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NASA NTRS1997

Experimental Studies of the Effect of Intent Information on Cockpit Traffic Displays

Intent information provides knowledge of another aircraft's current and future trajectory states. Prototype traffic displays were designed for four different levels of intent: Position, Rate, Commanded State, and FMS (Flight Management System)-Path. The current TCAS (traffic collision avoidance systems) Display, which shows altitude rate in addition to current position and altitude, was used as a baseline and represents the lowest level of intent. The Rate, Commanded State, and FMS-Path Displays show increasing levels of intent information using TCAS-like symbology in addition to incorporating a conflict probe and profile view display. An initial experiment was run on the MIT (Massachusetts Institute of Technology) Part Task Flight Simulator in which eight airline pilots flew five traffic scenarios with each of the four displays. Results show that pilots had fewer separation violations and maneuvered earlier with the three intent displays. Separation violations were reduced when pilots maneuvered earlier. A second experiment was run to compare performance between displaying intent information directly and incorporating it into a conflict probe. A different set of eight airline pilots flew four traffic scenarios with the TCAS and Commanded State Displays with and without the conflict probe. Conflict probes with two minute and long range look-ahead times were tested. Displaying conflict bands or showing intent information directly both led to fewer separation violations and earlier avoidance maneuvers than the base TCAS Display. Performance was similar between the two minute and long range look-ahead conflict probes. Pilots preferred all intent displays over the TCAS Display.

Barhydt, Richard↗

NASA NTRS1997

Experimental Studies of Intent Information on Cockpit Traffic Displays

Intent information provides knowledge of another aircraft's current and future trajectory states. Prototype traffic displays were designed for four different levels of intent: No Intent, Rate, Commanded State, and Flight Management System (FMS)-Path. The TCAS Display was used as a baseline and represents the No Intent Level. The Rate, Commanded State, and FMS-Path Displays show increasing levels of intent information using TCAS-like symbology in addition to incorporating a conflict probe and profile view display. An experiment was run on the MIT Part Task Flight Simulator in which eight airline pilots flew five traffic scenarios with each of the four displays. Results show that pilots had fewer separation violations and maneuvered earlier with the three intent displays. Separation violations were reduced when pilots maneuvered earlier. A second experiment was run to compare performance between displaying intent information directly and incorporating it into a conflict probe. A different set of eight airline pilots flew four traffic scenarios with the TCAS and Commanded State Displays with and without the conflict probe. Conflict probes with two minute and long range look-ahead times were tested. Displaying conflict bands or showing intent information directly both led to fewer separation violations and earlier avoidance maneuvers than the base TCAS Display. Performance was similar between the two minute and long range look-ahead conflict probes. Pilots preferred all intent displays over the TCAS Display.

Barhydt, Richard↗

NASA NTRS2012

Preliminary Benefits Assessment of Traffic Aware Strategic Aircrew Requests (TASAR)

While en route, aircrews submit trajectory change requests to air traffic control (ATC) to better meet their objectives including reduced delays, reduced fuel burn, and passenger comfort. Aircrew requests are currently made with limited to no information on surrounding traffic. Consequently, these requests are uninformed about a key ATC objective, ensuring traffic separation, and therefore less likely to be accepted than requests informed by surrounding traffic and that avoids creating conflicts. This paper studies the benefits of providing aircrews with on-board decision support to generate optimized trajectory requests that are probed and cleared of known separation violations prior to issuing the request to ATC. These informed requests are referred to as traffic aware strategic aircrew requests (TASAR) and leverage traffic surveillance information available through Automatic Dependent Surveillance Broadcast (ADS-B) In capability. Preliminary fast-time simulation results show increased benefits with longer stage lengths since beneficial trajectory changes can be applied over a longer distance. Also, larger benefits were experienced between large hub airports as compared to other airport sizes. On average, an aircraft equipped with TASAR reduced its travel time by about one to four minutes per operation and fuel burn by about 50 to 550 lbs per operation depending on the objective of the aircrew (time, fuel, or weighted combination of time and fuel), class of airspace user, and aircraft type. These preliminary results are based on analysis of approximately one week of traffic in July 2012 and additional analysis is planned on a larger data set to confirm these initial findings.

Henderson, Jeff↗

NASA NTRSDate not supplied

Separation Assurance in Urban Air Mobility Systems Using Shared Scheduling Protocols

Ensuring safe separation between aircraft is a critical challenge in air traffic management, particularly in urban air mobility (UAM) environments where high traffic density and low altitudes require precise control. In these environments, conflicts often arise at the intersections of flight corridors, posing significant risks. We propose a tactical separation approach leveraging shared scheduling protocols, originally designed for Ethernet networks and operating systems, to coordinate access to these intersections. Using a decentralized Markov decision process framework, the proposed approach enables aircraft to autonomously adjust their speed and timing as they navigate these critical areas, maintaining safe separation without a central controller. We evaluate the effectiveness of this approach in simulated UAM scenarios, demonstrating its ability to reduce separation violations to zero while acknowledging trade-offs in flight times as traffic density increases. Additionally, we explore the impact of non-compliant aircraft, showing that while shared scheduling protocols can no longer guarantee safe separation, they still provide significant improvements over systems without scheduling protocols.

Separation Assurance↗

NASA NTRSDate not supplied

Separation Assurance in Urban Air Mobility Systems Using Shared Scheduling Protocols

system safety↗

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 NTRS2010

Analysis of a Real-Time Separation Assurance System with Integrated Time-in-Trail Spacing

This paper describes the implementation and analysis of an integrated ground-based separation assurance and time-based metering prototype system into the Center-TRACON Automation System. The integration of this new capability accommodates constraints in four-dimensions: position (x-y), altitude, and meter-fix crossing time. Experiments were conducted to evaluate the performance of the integrated system and its ability to handle traffic levels up to twice that of today. Results suggest that the integrated system reduces the number and magnitude of time-in-trail spacing violations. This benefit was achieved without adversely affecting the resolution success rate of the system. Also, the data suggest that the integrated system is relatively insensitive to an increase in traffic of twice the current levels.

Aweiss, Arwa S.↗

NASA NTRSDate not supplied

A Human-In-The-Loop Simulation for Urban Air Mobility in the Terminal Area

In this paper researchers propose a human-in-the-loop experiment to study human performance when tasked with tactical deconfliction in terminal area air taxi operations. The air taxi operations being considered herein are an advanced air transportation concept called Urban Air Mobility (UAM). The UAM concept aims to support not only air taxi operations, but also package delivery and emergency response among other use cases. The key innovation over current air transportation lies with the introduction of highly automated aircraft and air traffic management systems. Development of the UAM system will include transitional midterm phases where some operational services will be provided by a mixture of automation and human actors. Midterm operations present a unique challenge, since the scope of responsibility of automated systems is largely undefined, suggesting the need for direct human participation with little to inform how much human intervention is necessary. Here it is assumed that traffic management responsibilities require coordination between human actors and automated systems and focus on arrival flows for midterm operations. In the proposed human-in-the-loop simulation, virtual UAM traffic is strategically deconflicted by a Provider of Services for UAM at departure, then tactically managed by a human at the arrival facility. Generated traffic consists of UAM participants flying in UAM exclusive airspace structures, thus isolated from traditional traffic. The human operator is tasked with managing spacing of arrival traffic and executing speed adjustments as deemed necessary. Researchers propose the investigation of three levels of automation assistance: 1) no assistance; 2) spacing violation detection; 3) spacing violation detection and speed adjustment recommendations. Quantitative measures like throughput and delay are used to assess the human's capacity for accommodating airborne delays. Qualitative evaluations such as surveys and open-ended feedback are used to gain insight into human factors. These factors could introduce additional capacity constraints on traffic, independent of physical or technical constraints. Although findings for this study will not be reported as the study has not yet been executed, the authors conclude with potential outcomes informed by previous simulations in the literature and suggestions for the structure and procedures of midterm human-automation air traffic management.

UAM↗

NASA NTRSDate not supplied

A Human-In-The-Loop Simulation for Urban Air Mobility in the Terminal Area

In this presentation we propose a human-in-the-loop experiment to study the potential impact of human engagement in tactical mitigation of delay in terminal area air taxi operations. The air taxi operations being considered herein is an advanced air transportation concept called Urban Air Mobility (UAM). The UAM concept aims to support not only air taxi operations, but also package delivery and emergency response among other use cases. The key innovation over current air transportation lies with the introduction of autonomous aircraft and autonomous air traffic management systems. Development of the UAM system will include transitional midterm phases where some operational services will be provided by a mixture of automation and human actors. Midterm operations present a unique challenge, since the scope of responsibility of automated systems is largely undefined, suggesting the need for direct human participation with little to inform how much human intervention is necessary. Here we assume that traffic management responsibilities require coordination between human actors and automated systems and focus on arrival flows for midterm operations. In the proposed human-in-the-loop simulation, virtual UAM traffic is strategically deconflicted by a Provider of Services for UAM at departure, then tactically managed by a human at the arrival facility. Generated traffic consists of UAM participants flying in UAM exclusive airspace structures, thus isolated from traditional traffic. The human operator is tasked with managing spacing of arrival traffic and executing speed adjustments as deemed necessary. We propose the investigation of three levels of automation assistance: 1) no assistance; 2) spacing violation detection; 3) spacing violation detection and speed adjustment recommendations. Quantitative measures like throughput and delay are used to assess the human's capacity for accommodating airborne delays. Qualitative evaluations such as surveys and open-ended feedback are used to gain insight into human factors. These factors could introduce additional capacity constraints on traffic, independent of physical or technical constraints. Although findings for this study will not be reported as the study has not yet been executed, we conclude with potential outcomes informed by previous simulations in the literature and suggestions for the structure and procedures of midterm human-automation air traffic management.

UAM↗

NASA NTRS2011

Trajectory-Based Complexity (TBX): A Modified Aircraft Count to Predict Sector Complexity During Trajectory-Based Operations

In this paper we introduce a new complexity metric to predict -in real-time- sector complexity for trajectory-based operations (TBO). TBO will be implemented in the Next Generation Air Transportation System (NextGen). Trajectory-Based Complexity (TBX) is a modified aircraft count that can easily be computed and communicated in a TBO environment based upon predictions of aircraft and weather trajectories. TBX is scaled to aircraft count and represents an alternate and additional means to manage air traffic demand and capacity with more consideration of dynamic factors such as weather, aircraft equipage or predicted separation violations, as well as static factors such as sector size. We have developed and evaluated TBX in the Airspace Operations Laboratory (AOL) at the NASA Ames Research Center during human-in-the-loop studies of trajectory-based concepts since 2009. In this paper we will describe the TBX computation in detail and present the underlying algorithm. Next, we will describe the specific TBX used in an experiment at NASA's AOL. We will evaluate the performance of this metric using data collected during a controller-inthe- loop study on trajectory-based operations at different equipage levels. In this study controllers were prompted at regular intervals to rate their current workload on a numeric scale. When comparing this real-time workload rating to the TBX values predicted for these time periods we demonstrate that TBX is a better predictor of workload than aircraft count. Furthermore we demonstrate that TBX is well suited to be used for complexity management in TBO and can easily be adjusted to future operational concepts.

trajectories↗

NASA NTRSDate not supplied

Aircraft Classification Using Radar from Small Unmanned Aerial Systems for Scalable Traffic Management Emergency Response Operations

This work investigates two machine learning techniques: Support Vector Machine (SVM) and Autoencoders (AE)with SVM layer for classification of radar trajectories as General Aviation (GA), fixed-wing small Unmanned Aerial System (sUAS), or not-an-aircraft using radar data recorded from sUAS. Onboard identification of intruder aircraft type is useful for planning avoidance maneuvers and is necessary to provide autonomous systems to meet or exceed the avoidance capability of a human pilot. Aircraft classification can identify intruder aircraft that are not part of the team and may be violating a Temporary Flight Restriction. Aircraft classification is needed in monitoring an airspace where multiple aircraft are teaming on a shared task. Scalable Traffic Management for Emergency Response Operations (STEReO) is a NASA project aimed at improving disaster response by enabling large scale aircraft operations through the teaming of manned aircraft with sUAS to maximize emergency response resources. To this end, this work uses trajectories and radar derived features to classify aircraft from a multirotor sUAS. The AE + SVM generated the strongest classification overall accuracy of 93.5% using the first 4 seconds of radar track data for tracks that activated the avoidance system. Subsampling the available track data increased the available training data with the maximum aircraft recall of 0.94 achieved using the SVM with 1 second track data.

Chester V. Dolph↗

DOE OSTI2021

Adaptive Protection of Scientific Backbone Networks Using Machine Learning

In this article, we propose a new protection scheme for backbone networks to guarantee high service availability. The presented scheme does not require any reconfiguration immediately after the failure (i.e., it is proactive). At the same time, it does not require any reserved backup network resources either. To achieve these seemingly contradictory goals, we utilize the recent advancements in Machine Learning (ML) to implement a network intelligence that periodically re-allocates the unused capacity as protection bandwidth to meet the service availability requirements of each connection. Our goal is achieved by two components (1) predicting the traffic for the next period on each link, and (2) intelligently selecting the best fit dedicated protection scheme for the next period depending on the estimated unused (spare) bandwidth and the previous service availability violations. Note that re-allocating protection bandwidth affects neither the operational connections nor the current best practice of operators to over-provision network bandwidth to support elephant flows. Finally, we provide a case study on the real traffic from Energy Sciences Network (ESnet), a high-speed, international scientific backbone network. The key benefit of our framework is that adaptively utilizing the over-provisioned bandwidth for spare capacity is sufficient to improve the availability from three-nines to five-nines (in ESnet for the 30 examined connections). The drawback is negligible bandwidth limitations; the user perceives a minor and very temporal bandwidth limitation in less than 0.1% of the time.

42 ENGINEERING↗

NASA NTRS1983

Primary separation between three aircraft using traffic displays

The use of a sophisticated traffic and map display termed electronic flight rules (EFR) by general aviation pilots for primary seperation in low density airspace is studied. The experimental flights were made under four conditions: with and without sensor noise in the traffic information and with and without communications for traffic coordination. Pilots were required to maintain two miles horizontal and 500 ft vertical separation from other aircraft for 24 different traffic situations repeated randomly for each of the four experimental conditions. Of 1152 aircraft encounters 12.8 percent were in violation of separation minimums. In general, the effects of sensor noise were minimal, communications affected some of the measures, and the group effect was quite significant. When pilots were able to communicate and coordinate their maneuvers, the time to resolve conflict was reduced.

Chappell, S. L.↗

NASA NTRSDate not supplied

Uncertainty Propagation in Pre-Flight Prediction of Unmanned Aerial Vehicle Separation Violation

Current forecasts on the future of aeronautics suggest an in- creasing number of unmanned aerial vehicles entering the low- altitude airspace in the next decades (FAA, 2018; Kopardekar et al., 2016). Small vehicles for package delivery as well as larger vehicles for urban air mobility will change the airspace drastically, increasing density of operations both in time, i.e. high number of take-off and landings per unit time, and in space, operating in dense urban environment. This scenario poses challenges to the current approach to air traffic control, and large efforts from academia, industry and regulatory bodies are dedicated to the development of new traffic management strategies that leverage higher computing and simulating capabilities available today. In this paper, we propose a simple look-ahead approach to predict potential minimum separation violations at the strategic level, that is before vehicles start flying, depending on the predefined 4D trajectories and uncertainty affecting the wind acting along those routes. The wind field is extracted from the NOAA North America Mesoscale Forecast System and interpolated using Gaussian process regression, while uncertainty affecting the expected cruise airspeed is propagated through error intervals. The approach allows the prediction of aircraft separation as a function of time, highlighting potential safety violations that would go undetected if uncertainty affecting the expected 4D trajectories is not considered. The paper will also discuss issues related to accuracy and scalability of the approach to multiple vehicle operations.

Trajectory Prediction↗

NASA NTRS1997

Conflict Detection and Resolution for Future Air Transportation Management

With a Free Flight policy, the emphasis for air traffic control is shifting from active control to passive air traffic management with a policy of intervention by exception. Aircraft will be allowed to fly user preferred routes, as long as safety Alert Zones are not violated. If there is a potential conflict, two (or more) aircraft must be able to arrive at a solution for conflict resolution without controller intervention. Thus, decision aid tools are needed in Free Flight to detect and resolve conflicts, and several problems must be solved to develop such tools. In this report, we analyze and solve problems of proximity management, conflict detection, and conflict resolution under a Free Flight policy. For proximity management, we establish a system based on Delaunay Triangulations of aircraft at constant flight levels. Such a system provides a means for analyzing the neighbor relationships between aircraft and the nearby free space around air traffic which can be utilized later in conflict resolution. For conflict detection, we perform both 2-dimensional and 3-dimensional analyses based on the penetration of the Protected Airspace Zone. Both deterministic and non-deterministic analyses are performed. We investigate several types of conflict warnings including tactical warnings prior to penetrating the Protected Airspace Zone, methods based on the reachability overlap of both aircraft, and conflict probability maps to establish strategic Alert Zones around aircraft.

Krozel, Jimmy↗

NASA NTRS2001

Aviation Safety Simulation Model

The Aviation Safety Simulation Model is a software tool that enables users to configure a terrain, a flight path, and an aircraft and simulate the aircraft's flight along the path. The simulation monitors the aircraft's proximity to terrain obstructions, and reports when the aircraft violates accepted minimum distances from an obstruction. This model design facilitates future enhancements to address other flight safety issues, particularly air and runway traffic scenarios. This report shows the user how to build a simulation scenario and run it. It also explains the model's output.

Houser, Scott↗

NASA NTRS1984

Influence of a perspective cockpit traffic display format on pilot avoidance maneuvers

Perspective projections of cockpit displays of traffic information (CDTI) on CRTs to present vertical separation information to airline pilots were examined. The perspective projection was compared with plan view projections of the same air traffic situations. Comparison of the pilots' avoidance maneuvers made when using the perspective display with those made while using more the conventional plan view display showed that pilots maneuvered somewhat earlier with perspective displays. With the perspective display, they maneuvered more frequently in the vertical dimension. The bias to maneuver horizontally probably reflected the poorer presentation of vertical separation on previously used plan view traffic displays. The avoidance decisions made by pilots using both perspective and plan view displays shows fewer unsuccessful maneuvers and fewer maneuvers producing spacing violations with the perspective format.

Ellis, S. R.↗

NASA NTRS2022

A Framework for Dynamic Architecture and Functional Allocations for Increasing Airspace Autonomy

To enable scalability of air travel for use cases such as cargo delivery, it is anticipated that future air traffic operations will involve unmanned aircraft operated by remote pilots. Of particular interest are schemes where a small number of pilots operate a large number of vehicles, mitigating high cost and pilot shortage issues. Such architectures require increased levels of automation and supervisory control modes. They also require ensuring safe operations when the command and control link to the vehicle is degraded or lost completely, rendering the vehicle autonomous. To evaluate these variable and dynamic architectures, this paper will present a framework for decomposing the functions necessary to ensure safe, orderly, and expeditious air travel, assessing the agents in the system, and classifying the levels of autonomy. Then, an example allocation to agents of roles for the function of separation assurance is presented, highlighting the dependency of the allocation on three main factors: time criticality of a potential separation violation, the ratio of pilots to vehicles, and the loss of the command and control link.

air traffic management, function allocation, auton↗