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At least 127 records · Page 7
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NASA NTRS2015

Strategic Planning of Efficient Oceanic Flights

The efficiency of oceanic flights is low due to limited navigational and communication equipment, congestion and airspace restrictions. The availability of Automated Dependent Surveillance-Broadcast (ADS-B) and other improvements provides opportunity for better strategic planning of trajectories. Transatlantic flights between US and Europe constitute one of the busiest oceanic airspace regions in the world. This paper examines the benefits of a wind-optimal trajectory concept with a strategic de-confliction component compared to the current flight planning using the North Atlantic Tracks. The methodology generates a wind-optimal route for each aircraft and a strategic reduction in the potential conflicts between aircraft by a combination of small adjustments to departure times and rerouting. The de-confliction is achieved by optimization techniques involving simulated annealing with local gradient searching. The fuel burn for the tracks in today's Organized Track System are compared with the corresponding quantities for the wind-optimized routes to evaluate the potential benefits of flying wind-optimal routes in North Atlantic Airspace. The analysis is based on air traffic between US and Europe during July 2012. The potential fuel savings depend on existing inefficiencies in current flight plans, atmospheric conditions and location of the city-pairs. The paper provides both aggregate results and detailed examination of some of the most popular city-pairs. Results show that strategic planning can improve the efficiency of flight trajectories by 3 to 5 depending on city-pairs and aircraft type. This translates into a potential fuel savings in the range of (420-970) kg per flight for a Boeing 767-300, the most widely used aircraft between the city-pairs in this study.

oceanic operations↗
NASA NTRS2019

Airborne Spacing for Terminal Arrival Routes (ASTAR) Proof-of-Concept Flight Test

The Airborne Spacing for Terminal Arrival Routes (ASTAR) Flight Test was conducted by the NASA Air Traffic Management Technology Demonstration – 1 (ATD- 1) project to demonstrate the use of NASA’s ASTAR algorithm beyond a simulated environment and assess the operational risks of performing a multi-aircraft flight test of Flight-deck Interval Management (FIM). Utilizing contemporary tools of the Federal Aviation Administration’s Next Generation Air Transportation System (NextGen) such as ADS-B, the ASTAR algorithm calculated speeds that the flight crew flew to achieve a precise spacing interval behind another aircraft at the final approach fix. Airspeed commands issued by the algorithm were flown by the flight crew of the FIM-equipped aircraft to achieve or maintain an assigned spacing goal from a target vehicle. The ASTAR algorithm was integrated with the Boeing supplied B-787 ecoDemonstrator aircraft, and five flight trials were conducted as a joint effort between NASA and Boeing on December 12, 2014. Initial results indicated arrival times within several seconds of accuracy of the planned termination point between two aircraft performing FIM in a real world environment. This flight test opened the way for the much more expansive ATD-1 Avionics Phase II flight test which occurred in early 2017. The flight trials under Phase II preceded further testing by the community in preparation for inclusion of the Interval Management concept as a part of the NextGen environment.

Roper, Roy D.↗
NASA NTRS2019

TAO Test Vector Evaluation Rev. 1

A group of encounter sets is evaluated as a standard for defining and refining both performance-based and functional-based terminal area MOPS requirements. DAIDALUS-alerting is used together with a variety of sensor configurations: (1) ADS-B level surveillance, (2) TCAS II, (3) ground-based RADAR with three different sets of error parameters.

Adami, Tony↗
NASA NTRS2019

Evaluation of Technology Concepts for Traffic Data Management and Relevant Audio for Datalink in Commercial Airline Flight Decks

Datalink is currently operational for departure clearances and in oceanic environments and is currently being tested in high altitude domestic enroute airspace. Interaction with even simple datalink clearances may create more workload for flight crews than the voice system they replace if not carefully designed. Datalink may also introduce additional complexity for flight crews with hundreds of uplink messages now defined for use. Finally, flight crews may lose airspace awareness and operationally relevant information that they normally pickup from Air Traffic Control (ATC) voice communications with other aircraft (i.e., “party-line” transmissions). Once again, automation may be poised to increase workload on the flight deck for incremental benefit. Datalink implementation to support future air traffic management concepts needs to be carefully considered, understanding human communication norms and especially, the change from voice- to text-based communications modality and its effect on pilot workload and situation awareness. Increasingly autonomous systems, where autonomy is designed to support human-autonomy teaming, may be suited to solve these issues. NASA is conducting research and development of increasingly autonomous systems, utilizing machine-learning algorithms seamlessly integrated with humans whereby task performance of the combined system is significantly greater than the individual components. Increasingly autonomous systems offer the potential for significantly improved levels of performance and safety that are superior to either human or automation alone. Two increasingly autonomous systems concepts - a traffic data manager and a conversational co-pilot - were developed to intelligently address the datalink issues in a complex, future state environment with significant levels of traffic. The system was tested for suitability of datalink usage for terminal airspace. The traffic data manager allowed for automated declutter of the Automatic Dependent Surveillance-Broadcast (ADS-B) display. The system determined relevant traffic for display based on machine learning algorithms trained by experienced human pilot behaviors. The conversational co-pilot provided relevant audio air traffic control messages based on context and proximity to ownship. Both systems made use of the connected aircraft concepts to provide intelligent context to determine relevancy above and beyond proximity to ownship. A human-in-the-loop test was conducted in NASA Langley Research Center’s Integration Flight Deck B-737-800 simulator to evaluate the traffic data manager and the conversational co-pilot. Twelve airline crews flew various normal and non-normal procedures and their actions and performance were recorded in response to the procedural events. This paper details the flight crew performance and evaluation during the events.

Etherington, Timothy↗
NASA NTRS2019

Sense and Avoid Characterization of the Independent Configurable Architecture for Reliable Operations of Unmanned Systems

Abstract—Independent Configurable Architecture for Reliable Operations of Unmanned Systems (ICAROUS) is a distributed software architecture developed by NASA Langley Research Center to enable safe autonomous UAS operations. ICAROUS consists of a collection formally verified core algorithms for path planning, traffic avoidance, geofence handling, and decision making that interface with an autopilot system through a publisher-subscriber middleware. The ICAROUS Sense and Avoid Characterization (ISAAC) test was designed to evaluate the performance of the onboard Sense and Avoid (SAA) capability to detect potential conflicts with other aircraft and autonomously maneuver to avoid collisions, while remaining within the airspace boundaries of the mission. The ISAAC tests evaluated the impact of separation distances and alerting times on SAA performance. A preliminary analysis of the effects of each parameter on key measures of performance is conducted, informing the choice of appropriate parameter values for different small Unmanned Aircraft Systems (sUAS) applications. Furthermore, low-power Automatic Dependent Surveillance – Broadcast (ADS-B) is evaluated for potential use to enable autonomous sUAS to sUAS deconflictions as well as to provide usable warnings for manned aircraft without saturating the frequency spectrum.

Consiglio, Maria↗
NASA NTRS2019

Airborne Radar for sUAS Sense and Avoid

A primary challenge for the safe integration of small UAS operations into the National Airspace System (NAS) is traffic deconfliction, both from manned and unmanned aircraft. The UAS Traffic Management (UTM) project being conducted at the National Aeronautics and Space Administration (NASA) considers a layered approach to separation provision, ranging from segregation of operations through airspace volumes (geofences) to autonomous sense and avoid (SAA) technologies for higher risk, densely occupied airspace. Cooperative SAA systems, such as Automatic Dependent Surveillance-Broadcast (ADS-B) and/or vehicle-to-vehicle communication systems provide significant additional risk mitigation but they fail to adequately mitigate collision risks for non-cooperative (non-transponder equipped) airborne aircraft. The RAAVIN (Radar on Autonomous Aircraft to Verify ICAROUS Navigation) flight test being conducted by NASA and the Mid-Atlantic Aviation Partnership (MAAP) was designed to investigate the applicability and performance of a prototype, commercially available sUAS radar to detect and track non-cooperative airborne traffic, both manned and unmanned. The radar selected for this research was a Frequency Modulated Continuous Wave (FMCW) radar with 120 degree azimuth and 80 degree elevation field of view operating at 24.55GHz center frequency with a 200 MHz bandwidth. The radar transmits 2 watts of power thru a Metamaterial Electronically Scanning Array antenna in horizontal polarization. When the radar is transmitting, personnel must be at least 1 meter away from the active array to limit nonionizing radiation exposure. The radar physical dimensions are 18.7cm by 12.1cm by 4.1cm and it weighs less than 820 grams making it well suited for installation on small UASs. The onboard, SAA capability, known as ICAROUS, (Independent Configurable Architecture for Reliable Operations of Unmanned Systems), developed by NASA to support sUAS operations, will provide autonomous guidance using the traffic radar tracks from the onboard radar. The RAAVIN set of studies will be conducted in three phases. The first phase included outdoor, ground-based radar evaluations performed at the Virginia Tech’s Kentland Farm testing range in Blacksburg, VA. The test was designed to measure how well the radar could detect and track a small UAS flying in the radar’s field of view. The radar was used to monitor 5 test flights consisting of outbound, inbound and crossing routes at different ranges and altitudes. The UAS flown during the ground test was the Inspire 2, a quad copter weighing less than 4250 grams (10 pounds) at maximum payload. The radar was set up to scan and track targets over its full azimuthal field of view from 0 to 40 degrees in elevation. The radar was configured to eliminate tracks generated from any targets located beyond 2000 meters from the radar and moving at velocities under 1.45 meters per second. For subsequent phases of the study the radar will be integrated with a sUAS platform to evaluate its performance in flight for SAA applications ranging from sUAS to manned GA aircraft detections and tracking. Preliminary data analysis from the first outdoor ground tests showed the radar performed well at tracking the vehicle as it flew outbound and repeatedly maintained a track out to 1000 meters (maximum 1387 meters) until the vehicle slowed to a stop to reverse direction to fly inbound. As the Inspire flew inbound tracks from beyond 800 meters, a reacquisition time delay was consistently observed between when the Inspire exceeds a speed of 1.45 meters per second and when the radar indicated an inbound target was present and maintained its track. The time delay varied between 6 seconds to over 37 seconds for the inbound flights examined, and typically resulted in about a 200 meter closure distance before the Inspire track was maintained. The radar performed well at both acquiring and tracking the vehicle as it flew crossing routes out past 400 meters across the azimuthal field of view. The radar and ICAROUS software will be integrated and flown on a BFD-1400-SE8-E UAS during the next phase of the RAAVIN project. The main goal at the conclusion of this effort is to determine if this radar technology can reliably support minimum requirements for SAA applications of sUAS. In particular, the study will measure the range of vehicle detections, lateral and vertical angular errors, false and missed/late detections, and estimated distance at closest point of approach after an avoidance maneuver is executed. This last metric is directly impacted by sensor performance and indicates its suitability for the task.

Szatkowski, George N.↗
NASA NTRS2010

TPSAS-NF1676L-10776-DND

Airborne self-separation (SSEP) among aircraft is proposed as a means for improving air traffic system capacity and safety in the future National Airspace System and for improving the efficiency of flight for all aircraft performing this function. The concept is examined in the U.S. en route domain, in an environment of mixed conventional and SSEP operations. No airspace is set aside for this purpose and the first aircraft equipped to perform the function can receive its benefits. For aircraft operating in the SSEP mode, the Air Navigation Service Provider (ANSP) turns over control and responsibility for all separation tasks to the pilots of SSEP aircraft. This includes separation from all other aircraft, from severe weather hazards and from Special Use Airspace. Connection to the centralized traffic flow management function is retained throughout the flight, however, and compliance with any Required Time of Arrival assignments is maintained. The SSEP function is accomplished in the aircraft through the use of airborne surveillance, data communications and processing equipment, and procedures defined in a new set of operating rules called "Autonomous Flight Rules" (AFR). The technical enablers are Automatic Dependent Surveillance - Broadcast (ADS-B), Traffic Information Service - Broadcast (TIS-B), and Traffic Alert and Collision Avoidance System (TCAS). This briefing presents an overview of the concept.

Frank Bussink↗
NASA NTRSDate not supplied

TPSAS-NF1676L-11456-DND

NASA’s precision scheduling and spacing research has matured to show the high potential of merging efficient flows in high density operations - Precision scheduling and efficient delay distribution minimizes early descent from enroute altitude and low-altitude vectoring - Precision merging and spacing control improves throughput - Enables the extended use of flight path optimization based procedures FAA/NASA/Industry collaboration is needed to accelerate implementation of ADS-B applications in a way that achieves the full benefit of NextGen operations to those that equip in high density airspace Integrated precision scheduling and spacing will to offer immediate and systematic benefits to airlines in many environments, even with different equipage levels and traffic densities

Harry Swenson↗
NASA NTRSDate not supplied

TPSAS-NF1676L-18030-DND

This study investigated the relative acceptance of different avionics implementations that present Flightdeck Interval Management (FIM) speeds and speed deviations to commercial pilots, and for indications of conditions that require action. Each crew evaluated four Avionics conditions: (1) Integrated in which the FIM target speed was presented in the upper left corner of the primary flight display (PFD) and speed profile deviation information was implicitly indicated as the deviation between current speed and an instantaneous speed profile bug on the PFD speed tape. In this Avionics condition, clearance information would have been entered, and could be referenced, on the FIM page in the MCDU. This page also gave a digital readout of speed profile deviation. Significant deviations from the speed profile triggered a message on the EICAS system. (2) EFB-Aft in which an aft-mounted EFB was used as the device housing the FIM algorithm and presented all the relevant information for the operation, including speed targets, speed deviation information, and all elements of the IM clearance. Significant deviations from the speed profile triggered messages on the same EFB display. (3) EFB-Fore in which the same information was presented as in the EFB-Aft condition, but the display was mounted in a more forward location, just under the outboard window. (4) EFB-Aft-AGD in which the EFB-Aft condition was augmented with the ADS-B Guidance Display (AGD). The AGD repeats the same FIM target speed and speed deviation information provided on the EFB. This study compares the efficacy of these Avionics Conditions as well as three methods of annunciating FIM events (a new speed, a reminder that a new speed occurred, and a deviation from the FIM speed profile), using only visual indications, visual indications and an aural for all events, or visual indications for all events plus an aural for speed deviations only. Results show clear preference for the Integrated condition and the use of aural indications. Other metrics of performance using these conditions and methods are mixed.

Kara Latorella↗
NASA NTRS2021

Evaluation of Sensor Uncertainty Mitigation Methods for Detect-and-Avoid Systems

The impact of sensor noise on the performance of Detect-And-Avoid (DAA) systems can be reduced by implementing various mitigation schemes. This paper evaluates two such methods. One of them is the Sensor Uncertainty Mitigation (SUM) method, implemented in the Detect and Avoid Alerting Logic for Unmanned Systems (DAIDALUS) algorithm, a reference implementation in the DAA minimum operational performance standards. The second method is the Virtual Intruder State Aggregation (VISA), which averages multiple subsequent intruder states extrapolated to the current (most recent) time into a single ``aggregated`` intruder state. The VISA method can be used either individually as a sensor noise mitigation method in its own right, or in combination with DAIDALUS SUM. The performance of these methods is evaluated using three safety and operational suitability metrics and compared with a baseline configuration using static safety buffers. A large number of encounters representative of low-speed unmanned aircraft against non-cooperative manned aircraft, not equipped with a broadcasting transponder or ADS-B out system, are simulated and evaluated. An air-to-air radar model produces representative sensor noise for the DAA system. Results show that increasing the DAIDALUS SUM parameters for horizontal and vertical uncertainty improves the safety metric at the cost of increasing the number of actionable alerts leading to increased workload. A range of SUM parameters is recommended as suitable values for the type of operations considered for this work. VISA was found to be almost as effective as other noise mitigation methods even when it was used alone. Combining VISA with DAIDALUS SUM achieved the best performance among all investigated methods used with DAIDALUS. General trends and optimal SUM configurations were found to be nearly the same for two large and very different encounter data sets.

Detect-and-Avoid Systems↗
NASA NTRS2022

An ODE-Fitting Approach to Estimate Critical Aircraft Performance Parameters for Trajectory Prediction

Ground-based decision support tools (DST) in air traffic management (ATM) typically perform trajectory prediction based on aircraft performance model (APM) parameters, but some or all of these parameters might not be readily available. In particular, the three critical parameters required for trajectory prediction are the thrust setting, drag coefficients, and takeoff weight of the aircraft. Unfortunately, these parameters are coupled and appear together in physics-based kinetic models. Past approaches utilize data from a specific phase of flight (climb, level flight or descent), where one or more of the parameters are assumed to be known and estimate the remaining unknown parameters. This approach introduces bias/errors and also does not extend to scenarios where all of the above parameters are not known with sufficient accuracy. This paper is the first of its kind to propose a generalized framework for simultaneous estimation of all three critical APM parameters (thrust, drag, and mass). The proposed approach utilizes data from both the climb and descent phases and fits the ordinary differential equation for altitude in each phase using historical trajectory data available from radar tracks or ADS-B. The approach yields a set of optimized APM parameters that are best suited to fit each historical flight record. The methodology is applied on on sample flights from three different aircraft types, and the results demonstrate low fit error and consequently will yield a high level of prediction accuracy.

trajectory prediction, aircraft performance model,↗
NASA NTRSDate not supplied

An ODE-Fitting Approach to Estimate Critical Aircraft Performance Parameters for Trajectory Prediction

Ground-based decision support tools (DST) in air traffic management (ATM) typically perform trajectory prediction based on aircraft performance model (APM) parameters, but some or all of these parameters might not be readily available. In particular, the three critical parameters required for trajectory prediction are the thrust setting, drag coefficients, and takeoff weight of the aircraft. Unfortunately, these parameters are coupled and appear together in physics-based kinetic models. Past approaches utilize data from a specific phase of flight (climb, level flight or descent), where one or more of the parameters are assumed to be known and estimate the remaining unknown parameters. This approach introduces bias/errors and also does not extend to scenarios where all of the above parameters are not known with sufficient accuracy. This paper is the first of its kind to propose a generalized framework for simultaneous estimation of all three critical APM parameters (thrust, drag, and mass). The proposed approach utilizes data from both the climb and descent phases and fits the ordinary differential equation for altitude in each phase using historical trajectory data available from radar tracks or ADS-B. The approach yields a set of optimized APM parameters that are best suited to fit each historical flight record. The methodology is applied on on sample flights from three different aircraft types, and the results demonstrate low fit error and consequently will yield a high level of prediction accuracy.

trajectory prediction↗
NASA NTRS2023

Safety Case for Small Uncrewed Aircraft Systems (sUAS) Beyond Visual Line of Sight (BVLOS) Operations at NASA Langley Research Center

This Technical Memorandum (TM) is written to provide for dissemination of the methods and safety considerations for operations of small Uncrewed Aerial Systems (sUAS) Beyond Visual Line-of-Sight (BVLOS)at NASA Langley Research Center. It includes the Safety Case used to acquire a BVLOS Certificate of Authorization (COA) from the FAA and is being published to enable others to benefit from this work. The intended operations, subject to approval from the Federal Aviation Administration (FAA) and the National Aeronautics and Space Administration (NASA), will include a combination of Within Visual Line of Sight (WVLOS) and Beyond Visual Line of Sight (BVLOS) flights, comprising of at most five sUAS operating concurrently, with no more than three operating BVLOS. Flights will occur in a subset of the Langley Air Force Base (LAFB) Class D airspace (KLFI) at a maximum altitude of 400 ft AGL. Most operations within this subset will take place in the City Environment Range Testing for Autonomous Integrated Navigation (CERTAIN) Range. The CERTAIN Range includes airspace inside the borders of NASA Langley Research Center (LaRC). Additional airspace over the northern section of CERTAIN will be requested as part of the Certificate of Authorization (COA). NASA LaRC BVLOS operations on the CERTAIN Range can be broken down into five critical components needed to meet the 14 CFR § 91.113 see and avoid requirement: 1) procedural deconfliction with LAFB for UAS operations at or below 400 ft and manned aircraft at or above 900’ AGL; 2) ground equipment for detection of intruder aircraft and to support communications between crewmembers ; 3) sUAS vehicles with advanced onboard automation capable of autonomously maintaining safe separation; 4) BVLOS standardized operating procedures (SOPs); 5) and personnel to execute the flight operations in accordance with the SOPs and respond to airborne contingencies. The introduction of new ground equipment includes the use of the Remote Operations for Autonomous Missions (ROAM) UAS Operations Center, development and use of an Integrated Airspace Display (IAD), use of the L-STAR and GA-9120 radars, and the incorporation of standardized Vertiports. The ROAM Operations Center will be the central point for all BVLOS sUAS operations. All command and control (C2), voice communications and airspace awareness displays will reside inside ROAM. The IAD will provide raw data from ADS-B, FLARM, radar tracks and telemetered GPS vehicle positions for interpretation by an Airspace Monitor. The radars will search the class D airspace around the CERTAIN Range and serve as a backup to procedural deconfliction procedures coordinated with LAFB. In the event of a procedural deconfliction breakdown, radar detections of non-participating aircraft will be available so that the 91.113 see and avoid requirement can still be safely met. Finally, the incorporation of Vertiports will have video and network connectivity that enables large numbers of sUAS launches and recoveries from a single location. This is a continuation of the remote command and control of unpiloted aircraft component focused on evaluating unpiloted aircraft flight crew roles and responsibilities, control interfaces and the associated data links needed to operate a fleet of aircraft within a UAM Ecosystem. This work supports the development of future aviation operational concepts based on an Urban Air Mobility Maturity Level (UML) 4 environment (Patterson, 2020). It is assumed that future airspace will include hundreds of simultaneous aircraft operations within the airspace, therefore scalable operations are essential for enabling this future airspace to become a reality. Follow on work includes envisioned flights that expand operations beyond the CERTAIN range and lead to an effective Maritime Surveillance capability.

Matthew W Coldsnow↗
NASA NTRSDate not supplied

Formalized Reasoning of Operational Volumes for Wildland Fire Fighting

This work is focused on the formalized reasoning of operational volumes as it relates to the current and future technologies developed by NASA to aid in wildfire fighting operations. One such technology is the unmanned aircraft system pilot kit (UASP-kit) developed by the Scalable Traffic Management for Emergency Response Operations (STEReO) project at NASA, which is used to increase situation awareness for a ground operator in the field. The UASP-kit utilizes operational volumes which represent mission areas and alerting volumes, to alert when another aircraft is within one of these volumes from received ADS-B data. This work is focused on developing a rigorous foundation for the concept of operational volumes for modeling and prototyping operations in such a tool as the UASP-kit. This includes establishing a class of algorithms to detect when an object is in an operational volume, and when an operational volume is intersecting or contained within another. Additionally, this work is focused on providing rigorous proof in an interactive theorem prover that the algorithms work as intended. Scenarios are presented that model current UASP-kit operations and extend past the current capabilities of the technology to modeling more complex scenarios such as mission planning.

Operational Volumes↗
NASA NTRSDate not supplied

Formalized Reasoning of Operational Volumes for Wildland Fire Fighting

This work is focused on the formalized reasoning of operational volumes as it relates to the current and future technologies developed by NASA to aid in wildland firefighting operations. One such technology is the Unmanned Aircraft System Pilot Kit (UASP-kit) developed by the Scalable Traffic Management for Emergency Response Operations (STEReO) project at NASA, which is used to increase situational awareness for a ground operator in the field. The UASP-kit utilizes operational volumes to represent mission areas and alerting volumes; these volumes, in combinations with ADS-B data, can then be used to alert the ground operator when another aircraft has entered one of these areas. This work presents a rigorous foundation for the concept of operational volumes for modeling and prototyping operations in such a tool as the UASP-kit. This includes establishing a class of algorithms to detect when an object is in an operational volume, and when one operational volume intersects or is contained in another. Additionally, this work provides rigorous proof that the algorithms work as intended. Scenarios are presented that model current UASP-kit operations and extend past the current capabilities of the technology to modeling more complex scenarios such as mission planning.

Operational Volumes↗
NASA NTRSDate not supplied

Detect and Avoid and Collision Avoidance Flight Test Results with ACAS Xr

In October 2023, the National Aeronautics and Space Administration (NASA) completed its Integration of Automated Systems flight test series, conducted under NASA’s Advanced Air Mobility project and in partnership with Sikorsky and the Defense Advanced Research Projects Agency (DARPA). The flight test effort included two crewed rotorcraft platforms. The first, a modified S-76B helicopter, served as the “ownship” for the duration of the flight test. The second vehicle, a modified S-70, served as the intruder aircraft. One Sikorsky pilot and one NASA test pilot was onboard each aircraft for every test point, with the NASA test pilot responsible for interacting with the research systems under test. Approximately half of the flight test was devoted to assessing the Federal Aviation Administration’s (FAA) next-generation collision avoidance system, the Airborne Collision Avoidance System X for Rotorcraft (ACAS Xr). The two configurations available within ACAS Xr – the Collision Avoidance System (CAS) configuration and the Detect and Avoid (DAA) configuration – were flown with an onboard pilot under Visual Flight Rules in controlled airspace over the Long Island Sound (Connecticut, USA). A total of 33 flight test cards were flown with ACAS Xr active. The ownship was equipped with ACAS Xr and the intruder was equipped with Automatic Dependent Surveillance-Broadcast (ADS-B). The test points were blocked by ACAS Xr configuration, with individual encounters varying the ownship speed (90 knots or 20 knots), the intruder designation (en-route, terminal area, or structured airspace), and method of RA execution (automated or manually executed). Results showed that the ACAS Xr alerting and guidance was largely effective and rated positively by the NASA test pilots, exemplified by zero instances of the pilots overriding an ACAS Xr Resolution Advisory (RA). Key areas of improvement, however, were noted, particularly with regards to the lack of an aural alert indicating a need to accelerate when receiving an RA at low speed and the occurrence of multiple RAs that the pilots found to be unacceptable.

detect and avoid↗
NASA NTRSDate not supplied

Detect and Avoid and Collision Avoidance Flight Test Results with ACAS Xr

In October 2023, the National Aeronautics and Space Administration (NASA) completed its Integration of Automated Systems flight test series, conducted under NASA’s Advanced Air Mobility project and in partnership with Sikorsky and the Defense Advanced Research Projects Agency (DARPA). The flight test effort included two crewed rotorcraft platforms. The first, a modified S-76B helicopter, served as the “ownship” for the duration of the flight test. The second vehicle, a modified S-70, served as the intruder aircraft. One Sikorsky pilot and one NASA test pilot was onboard each aircraft for every test point, with the NASA test pilot responsible for interacting with the research systems under test. Approximately half of the flight test was devoted to assessing the Federal Aviation Administration’s (FAA) next-generation collision avoidance system, the Airborne Collision Avoidance System X for Rotorcraft (ACAS Xr). The two configurations available within ACAS Xr – the Collision Avoidance System (CAS) configuration and the Detect and Avoid (DAA) configuration – were flown with an onboard pilot under Visual Flight Rules in controlled airspace over the Long Island Sound (Connecticut, USA). A total of 33 flight test cards were flown with ACAS Xr active. The ownship was equipped with ACAS Xr and the intruder was equipped with Automatic Dependent Surveillance-Broadcast (ADS-B). The test points were blocked by ACAS Xr configuration, with individual encounters varying the ownship speed (90 knots or 20 knots), the intruder designation (en-route, terminal area, or structured airspace), and method of RA execution (automated or manually executed). Results showed that the ACAS Xr alerting and guidance was largely effective and rated positively by the NASA test pilots, exemplified by zero instances of the pilots overriding an ACAS Xr Resolution Advisory (RA). Key areas of improvement, however, were noted, particularly with regards to the lack of an aural alert indicating a need to accelerate when receiving an RA at low speed and the occurrence of multiple RAs that the pilots found to be unacceptable.

detect and avoid↗