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NASA NTRSDate not supplied

Integrating Upper Class E Traffic Management (ETM) Operations into the National Airspace System: Use Cases and Research Questions

As new categories of vehicles are introduced in the National Airspace System, so too are novel concepts for a cooperative approach to traffic management environments. One of these new environments, Upper Class E Traffic Management (ETM), is expected to include a variety of high altitude, long endurance vehicles with a range of performance capabilities and mission profiles that operate in cooperative areas above 60,000 feet. In addition to developing the rules, architecture, and systems for operations within the ETM environment itself, it is also important to consider how ETM vehicles will integrate with traditional Air Traffic Management and interact with Air Traffic Control (ATC) as they traverse ATC-controlled airspace and transition in and out of cooperative ETM operating areas. As a first step toward future ETM demonstrations at the National Aeronautics and Space Administration (NASA) Ames Research Center’s Airspace Operations Laboratory, use cases with step-by-step procedures were developed to identify both nominal and off-nominal scenarios in which ETM operations will interact with ATC. As NASA prepares to develop a simulation platform to demonstrate ETM cooperative practices and ETM-ATC interactions, the procedures, ATC roles and responsibilities, data exchange requirements, and research questions that were identified as part of use case development will inform scenario and system architecture design. The upcoming simulation work will include initial prototype ETM-ATC coordination tools to support ATC controllers’ interactions with ETM operations. This paper will briefly discuss NASA’s upcoming ETM development work and then provide background on ETM-ATC interactions, describe each ETM-ATC interaction use case, and discuss open questions on concept, procedures, and assumptions.

ATC↗

NASA NTRS2023

Concept of Operations for an In-time Aviation Safety Management System (IASMS) for Upper E Airspace

The National Airspace System undergoes continuous change including in the Upper Class E airspace involving increasingly complex operations and a widening diversity of vehicles. To secure a safe future system, the National Academies recommended an In-time Aviation Safety Management System (IASMS) that is extensible to Upper E. Current Air Traffic Management is not cost-effective to scale for future Upper E operations and diversity of vehicles so the Federal Aviation Administration developed an Upper E Traffic Management ConOps to safely integrate the diverse operations and vehicles having different performance characteristics and flight missions without disrupting current operations including space launch and reentry, suborbital flights, supersonic and hypersonic flights, slow moving or stationary unmanned balloons, and long endurance fixed wing vehicles that are slow, stationary, or high speed. IASMS integrates state-of-the-art predictive modeling with reactive and proactive analytics to detect hazards and mitigate risk precursors for Upper E operators. IASMS identifies emergent safety risks exposed by transformation of the NAS with new and increasingly complex operations. Safety intelligence will also expand the data available and offer insight to new approaches for implementing safety improvements to mitigate risk with more seamless “in-time” integration across the policy, risk management, safety assurance, and promotion pillars of SMS.

K Ellis↗

NASA NTRSDate not supplied

Focus Group Study of US Pilots on Fatigue in Short-Haul Flight Operations

Introduction: There are few studies investigating the impact of fatigue in short-haul flight operations conducted under United States (US) Federal Aviation Regulations (FAR) Part 117 flight and duty limitations and rest requirements. In order to understand the fatigue factors unique to short-haul operations, we conducted a series of focus groups across four major commercial passenger airlines in the US. The outcomes of this study were intended to inform the scope of a larger study of fatigue in short-haul operations. Methods: Ninety short-haul pilots were recruited through emails distributed by airline safety teams and labor representatives. Fourteen focus groups were conducted via an online conferencing platform in which participants were asked to identify, specific to short-haul: a) schedules and operations that lead to elevated fatigue; b) schedules and operations that are not fatiguing, and c) important fatigue factors to study. Data were collected anonymously and coded using conventional qualitative content analysis, with axial coding and summative analysis used to identify main themes and over-arching categories. Results: Participants had an average of 12,348 (6,483) lifetime flying hours with 71 (14.5) hours of monthly flying. Forty-six percent of participants were captains. The six fatigue factor categories identified were: circadian disruption (e.g., circadian switches, redeyes), high workload (e.g., hassle factors, number of flights per duty), inadequate rest opportunity (e.g., minimum rest layovers, quality of rest facilities), schedule changes (e.g., unpredictability), regulation and policy issues (e.g., scheduling up to FAR 117 limits), and long sits (e.g., long wait times between flights). Discussion: A field study informed by these results and designed to investigate the prevalence and impact of these factors in US short-haul operations is currently underway.

aviation↗

NASA NTRS2022

Remote Diagnosis and Operational Response to an In-Flight Failure of the Drill Feed Mechanism Onboard the Mars Science Laboratory Rover

On November 30th, 2016 (Sol 1536 of the mission), the Mars Science Laboratory (MSL) flight operations team commanded the Curiosity rover to drill into a Martian rock to acquire the mission’s 16th rock powder sample. The drilling operation was halted when the drill feed mechanism unexpectedly stalled shortly after disengaging its magnetically-actuated friction brake at the start of a long move to extend the drill bit into contact with the target rock. The drilling campaign was put on hold and later abandoned as diagnostic experimentation revealed a tendency for the actuator to transition in and out of a high-drag state in which the mechanism could not actuate. In the subsequent months, the team conducted a variety of in-flight and ground-based investigations to determine root cause and identify mitigation strategies for continued operation. Mechanism reliability continued to degrade and by June 2017, it became clear that the mechanism could not be relied upon to support drilling operations. The team succeeded in fully extending the feed, enabling the development of new sampling techniques that would not rely on the feed mechanism. The first feed-extended drilling sample was successfully collected on Sol 2057, 521 sols after the initial feed stall. This paper discusses the anomaly investigation process, failure analysis, and feed mechanism operation mitigation strategies. It concludes with key lessons learned about mechanism design, mission architecture, and operational best practices.

Lin, Megan Richardson↗

NASA NTRS2022

Fatigue in Short-Haul Operations: Regulations and Research

Short-haul multi-segment flight operations are conducted within Part 117 table limits for Flight Time and Flight Duty Period, yet there are few data available regarding the impact on sleep, workload, and performance in these operations. The Civil Aerospace Medical Institute (CAMI) has invested in the planning and execution of a study that will result in data characterizing the effects of short-haul multi-segment flight operations on cumulative sleep loss and pilot workload across trip pairings. Scientific researchers from CAMI, in collaboration with NASA Ames Research Center, are currently running an operational field study to examine the human factors and elements of pilot performance associated with short-haul multi-segment flight operations to better understand the impact of sleep disruption and workload across trip pairings. The first half of this presentation will provide a brief overview of current duty and rest requirements and identify gaps in current operational research data. The second half of the presentation will focus on results from a focus group study which developed the scope of the larger field study, followed by an overview of the current field study.

short-haul↗

NASA NTRS2023

Search for UnderUtilized Airspace for Extensible Traffic Management Operations Based on Air Traffic Patterns

This paper presents a new method to facilitate integrating new vehicle traffic operations, operating with existing air traffic operations. The extensible traffic management (xTM) concept assumes that the new vehicles can operate in a dedicated Cooperative Area (CA) with minimal interaction with conventional air traffic and requiring minimal air traffic supervision. Our method assumes that a new xTM CA can be created when an underutilized airspace with little or no traffic can be identified. Our approach involves modeling airspace as a tree data structure and iteratively subdividing it into smaller cells, with underutilized airspace defined as any cells without flight tracks. The benefits of our approach include its applicability to all xTM scenarios, the ability to handle both 2D and 3D space using a unique tree data structure, and computational efficiency for key functions such as space decomposition, labeling of connected cells, and searching of cells containing a given point. By automatically searching for underutilized airspace based on operating air traffic patterns, we can optimize airspace utilization and improve air traffic management. Our proposed approach can quantitatively determine when and where to allow xTM operations in the National Airspace System.

extensible traffic management↗

NASA NTRSDate not supplied

The View From the Flight Deck: Pilot Perspectives on Fatigue in Short-Haul Operations

INTRODUCTION: There are few studies investigating the impact of fatigue in short-haul flight operations conducted under United States (US) Federal Aviation Regulations (FAR) Part 117 flight and duty limitations and rest requirements. In order to understand the fatigue factors unique to short-haul operations, we conducted a series of focus groups across four major commercial passenger airlines in the US. The outcomes of this study were intended to inform the scope of a larger study of fatigue in short-haul operations. METHODS: Ninety short-haul pilots were recruited through emails distributed by airline safety teams and labor representatives. Fourteen focus groups were conducted via an online conferencing platform in which participants were asked to identify, specific to short-haul: a) schedules and operations that lead to elevated fatigue; b) schedules and operations that are not fatiguing, and c) important fatigue factors to study. Data were collected anonymously and coded using conventional qualitative content analysis, with axial coding and summative analysis used to identify main themes and over-arching categories. RESULTS: Participants had an average of 12,348 (6,483) lifetime flying hours with 71 (14.5) hours of monthly flying. Forty-six percent of participants were captains. The six fatigue factor categories identified were: circadian disruption (e.g., circadian switches, redeyes), high workload (e.g., hassle factors, number of flights per duty), inadequate rest opportunity (e.g., minimum rest layovers, quality of rest facilities), schedule changes (e.g., unpredictability), regulation and policy issues (e.g., scheduling up to FAR 117 limits), and long sits (e.g., long wait times between flights). DISCUSSION: A field study informed by these results and designed to investigate the prevalence and impact of these factors in US short-haul operations is currently underway.

aviation↗

NASA NTRSDate not supplied

Airspace Performance Observations of Scalable Autonomous Operations in a High Density Vertiplex Simulation

The National Aeronautics and Space Administration’s (NASA’s) High Density Vertiplex (HDV) subproject aims to develop and demonstrate progressive automation technologies that contribute to the Advanced Air Mobility (AAM) concept. Using Human-and-Hardware-In-TheLoop (HHITL) techniques, HDV demonstrates initial vertiport automation services at vertiports with increased air traffic volume in both simulated and live test environments. In 2023, the Scalable Autonomous Operations (SAO) simulation was conducted in which prototype vertiport, airspace, and ground control station technologies were assessed on technical performance. During the SAO simulation, an observational study captured an initial impression of the HDV airspace performance, potential disruptions to the airspace, and highlighted some capability and procedural gaps. Observations took place in two parts. In the first part, five scenario use cases (Nominal, Missed Approach, Speed Change, Divert, and MultiAircraft Divert) were conducted with three human operator roles (Vertiport Manager, Fleet Manager, and Ground Control Station Operator). Researchers collected metrics on throughput, closest point of approach, and airborne delay. In the second part of the study, the Missed Approach scenario was observed under three traffic density levels (20, 40, and 60 operations per hour) to challenge the automation to correctly identify slots in the vertiport arrival schedule. The results showed that the automation successfully found a slot for the Missed Approach vehicle in the 20 operations per hour condition, after some delay it found one in the 40 condition, and it did not find one in the 60 condition. The observations of technical and human performance throughout the five scenario use cases and the Missed Approach case study indicated that for HDV to increase traffic density and maintain or increase throughput, airspace monitoring services should be able to detect and resolve conflicts between aircraft. Furthermore, the roles and responsibilities of human operators need additional definition when it comes to responding to vehicle conflicts.

Advanced Air Mobility↗

NASA NTRSDate not supplied

Airspace Performance Observations of Scalable Autonomous Operations in a High Density Vertiplex Simulation

The National Aeronautics and Space Administration’s (NASA’s) High Density Vertiplex (HDV) sub- project aims to develop and demonstrate progressive automation technologies that contribute to the Advanced Air Mobility (AAM) concept. Using Human-and-Hardware-In-The- Loop (HHITL) techniques, HDV demonstrates initial vertiport automation services at vertiports with increased air traffic volume in both simulated and live test environments. In 2023, the Scalable Autonomous Operations (SAO) simulation was conducted in which prototype vertiport, airspace, and ground control station technologies were assessed on technical performance. During the SAO simulation, an observational study captured an initial impression of the HDV airspace performance, potential disruptions to the airspace, and highlighted some capability and procedural gaps. Observations took place in two parts. In the first part, five scenario use cases (Nominal, Missed Approach, Speed Change, Divert, and Multi- Aircraft Divert) were conducted with three human operator roles (Vertiport Manager, Fleet Manager, and Ground Control Station Operator). Researchers collected metrics on throughput, closest point of approach, and airborne delay. In the second part of the study, the Missed Approach scenario was observed under three traffic density levels (20, 40, and 60 operations per hour) to challenge the automation to correctly identify slots in the vertiport arrival schedule. The results showed that the automation successfully found a slot for the Missed Approach vehicle in the 20 operations per hour condition, after some delay it found one in the 40 condition, and it did not find one in the 60 condition. The observations of technical and human performance throughout the five scenario use cases and the Missed Approach case study indicated that for HDV to increase traffic density and maintain or increase throughput, airspace monitoring services should be able to detect and resolve conflicts between aircraft. Furthermore, the roles and responsibilities of human operators need additional definition when it comes to responding to vehicle conflicts.

advanced air mobility↗

NASA NTRSDate not supplied

Initial Study of Tailored Trajectory Management for Multi-Vehicle Uncrewed Regional Air Cargo Operations

The primary contribution of this paper is an evaluation of the potential value of a tailored trajectory management (TTM) capability for uncrewed aircraft (UA) operators that is proactive in detecting conflicts and developing trajectory-based solutions for UA prior to air traffic control (ATC) performing conflict resolution. The experiment matrix is composed of one baseline simulation that models current air traffic operations without such a capability and four test simulations with different configurations of such a capability. In each simulation, five UA operations into Fort Worth Alliance airport were modeled in the presence of recorded tracks for about 4700 flights on January 18, 2022. The analysis focused on the extent to which such a capability was able to preclude an event that could spike UA operator workload. More specifically, in this study, the emulated UA operator TTM capability for multi-vehicle regional air cargo operations was able to reduce the number of instances of concurrent UA conflicts in the modeled ATC conflict resolution timeframe of 8 minutes or less from three to as low as one.

uncrewed aircraft, regional air cargo, tailored tr↗

NASA NTRS2024

Testing of Advanced Capabilities to Enable In-time Safety Management and Assurance for Future Flight Operations

In order to refine an initial Concept of Operations, explore Concepts of Use, and expose/validate requirements for future In-Time Aviation Safety Management Systems (IASMS), testing architectures were created, along with a set of capabilities and underlying information exchange protocols. These systems were conceived and developed based on hazards associated with two envisioned urban area flight domains: (1) highly autonomous small uncrewed aerial systems (sUAS) operating at low altitudes, and (2) highly autonomous air taxis. The initial scope of this development is described in [1]; this report provides an update, focusing on the subsequent developments and test activities. As stated in [1], it is important to note that there are many capabilities already in use by the industry (or soon to be in use) that will play critical roles in future IASMS designs. Those reported here were developed to address a gap in the current state-of-the-art regarding specific hazards/risks, and/or to allow for investigation of the interplay between and across hazard types — particularly regarding how overall safety risk can be reduced or managed effectively. Results of testing and development activities are organized by the operational phase wherein a particular capability would be employed (i.e., preflight, in-flight, and post-flight/off-line). Pre-flight: A set of capabilities were developed to help mitigate safety risk prior to flight (e.g., during flight and mission planning). Results of testing summarize (1) validation activities to raise the Technology Readiness Level (TRL) and (2) evaluation activities where the capabilities were applied to flight/mission planning procedures and used by operators/pilots. For the latter, flight plans were automatically assessed, and operators/pilots were notified of hazardous flight segments so as to enable adjustment of the flight plan and re-evaluation, and/or to better inform go/no-go decisions. Capabilities addressed hazards associated with power consumption, third-party risk, wind, navigation system performance, radiofrequency interference, and proximity to geo-spatial threats (e.g., buildings, trees, and no-fly zones). In-flight: Flight experiments tested capabilities that detect and respond to hazards encountered during flight. In the first series, safety hazards were monitored and assessed onboard, and system-generated mitigation maneuvers were recorded (but not acted upon by the vehicle). In the second series, mitigation maneuver commands directed the aircraft in response to safety hazards (i.e., auto-mitigation). The sUAS used for testing is described in full, as is the test architecture, which included commercial avionics, research avionics, and onboard software designed to detect, assess, and respond to hazards. The onboard system was designed as a run-time assurance framework, consistent with [2] and supportive of both supervisory and automated modes. The primary functions included: real-time risk assessment (RTRA), auto-pilot monitoring, constraint monitoring, and contingency select/triggering. RTRA performs integrated risk assessment considering data from several hazard-related monitors (e.g., battery, motors, navigation, communications, population density, and loss-of-control). Post-flight/off-line: Data monitored and recorded during flights can enable IASMS capabilities that execute after flights have completed (or “off-line”). These include: (1) the ability to identify anomalies and trends that may only be observable when comparing data spanning a number of similar flights; (2) the ability to update and validate pre-flight and in-flight capabilities and any underlying models to improve their performance; (3) the ability to report anomalies/off-nominals that may indicate design changes or maintenance actions are needed; and (4) the ability for humans involved in operations to report safety-relevant observations to help in understanding the flight data and/or the operational context of a flight. Progress on three such capabilities is summarized; the first investigates anomaly detection given a limited set of flight logs and applies an approach previously used for space operations. The second explores what could be identified using a larger set of flight logs, including from web-based forums where flight logs are posted by sUAS autopilot users. The third creates a new means of collecting information on UAS incidents and accidents via the Aviation Safety Reporting System (ASRS).

sUAS↗

NASA NTRSDate not supplied

Analyzing Launch Operations using the Spaceport Throughput Analysis Resource (STAR)

NASA’s Kennedy Space Center (KSC) and Cape CanaveralSpace Force Station (CCSFS) are the world’s preeminent multi-user spaceport, providing facilities and launch capabilities to the agency, NASA’s commercial partners, and other government agencies. KSC works to ensure an environment in which NASA’s programs and other users can safely and effectively carry out their operations. Approximately 100 launches are expected to take place in 2024. KSC needs to meet the needs of customers who request launches based on their own schedules, but who may not be aware of KSC-wide resource limitations and external constraints on launch operations. KSC-wide resources include telecommunications, range tracking, commodities such as Helium and Nitrogen, and special equipment needed to support launches. External constraints include seasonal launch operations. Since space vehicles are complex and launch operations are uncertain, unexpected events can also cause delays in operations. The Spaceport Throughput AnalysisResource (STAR) assesses whether a specific set of pro-posed launches and associated activities can be performed given the resources KSC currently has available, and external constraints imposed on KSC operations. STAR integrates short-horizon scheduling and simulation of launches using a monte-carlo approach driven by configurable probabilities of different classes of event outcomes, including de-lays and worst-case use of resources. The resulting analyses inform stakeholders of key constraints preventing customers from being able to perform their missions as desired, and give insight into how to improve spaceport throughput. The rest of the paper is organized as follows. In 2 we de-scribe the problem STAR is intended to solve. In Section3 we formally describe the scheduling problem ingredients. In Section 4 we describe how manifests are simulated. InSection 5 we describe the constraints problem that is solved when rescheduling. In Section 6 we describe what information is recorded during manifest simulation in order to evaluate delays. In Section 7 we describe the specific problem solved for KSC. In Section 8 we describe the challenges of knowledge engineering for STAR.

Planning Scheduling Analysis↗

NASA NTRSDate not supplied

System-Wide Error Attribution in Multi-Vehicle Operations: Theoretical Explanation, Implications, and Applications

In multi-vehicle aerial operation contexts, a single or several human operators (m) are responsible for managing multiple uncrewed vehicles (N). This is referred to as the m:N operational paradigm. When automation error occurs during m:N operations, especially if multiple vehicles exhibit automation error, a question is raised: What level of system globality will the error be attributed to? Globality refers to the levels within the conceptual hierarchy of a perceptual object. Significant costs could be incurred if the error is falsely attributed to a higher globality level than it should be (e.g., multiple groups of vehicles as opposed to a single vehicle), and those vehicles are subsequently subject to grounding and evaluation/maintenance. Likewise, it could be problematic if error is falsely attributed to a component (i.e., a lower globality level), resulting in ongoing, unsafe operation of vehicles that should be grounded or evaluated. Thus, to meet required safety standards and facilitate commercial viability, multi-vehicle operators must be capable of appropriately attributing the level of globality of automation error within the system they are responsible for.

Error↗

NASA NTRSDate not supplied

A Queuing Theory Approach to Pilot-Controller Coordination for m:N Operations

In recent years, attention and interest by industry and researchers has grown in a control paradigm for remotely piloted aircraft termed “m:N operations.” In an m:N operation, a team of m remote pilots in command (RIPCs) collaboratively manage the flights of N aircraft. A consequence of an m:N concept of operations is that the RPICs will have to switch attention from one aircraft to another and from one task to another. Previous research in m:N operations has focused on the workload experienced by an RPIC and their level of situation awareness on their flights. Researchers have found that RPIC workload and situation awareness are generally sensitive to increasing N, although NASA’s Multi-Vehicle (m:N) Working Group has suggested that the driver of workload/situation awareness is the number of exceptions requiring human intervention as opposed to the value of N itself. In any case, a natural antecedent of workload is task load. In this paper, queueing theory is applied to a 1:N Urban Air Mobility (UAM) air taxi operation in order to estimate pilot task load for managing radio communications with air traffic controllers (ATCs) under increasing N. An M/M/1 queueing system is used to model the RIPC’s servicing of calls and clearance requests (e.g., departure, arrival, or airspace transition) to ATC for the N aircraft. Important parameters for the queueing model are the task arrival rate and the average service time for task completion. Radio communication times from past human-in-the-loop simulation studies are used to measure service times for a 1:4 and 1:12 UAM operation and to interpolate service times for 4 < N < 12. A Monte Carlo method is then employed, using the measured and interpolated service times, to estimate arrival rate and related queueing statistics. The paper concludes by considering the estimated queuing statistics, particularly the RPIC’s utilization (i.e., proportion of time actively servicing tasks), the length of the task queue over time, and the implications for task-balanced system design.

task load↗

NASA NTRSDate not supplied

Plume Impingement Software Module for Real-Time Proximity Operations

Successfully executing proximity operations in space, such as docking or in-orbit servicing, requires sophisticated spacecraft design that accounts for induced environments. As a chaser vehicle’s attitude control thrusters fire, they create rarefied plumes that can impact the target vehicle, with the potential to overload components, exceed thermal limits, and spin the target vehicle out of control. High-fidelity simulations of the thruster plume impingement environment require the direct simulation Monte Carlo (DSMC) method, but DSMC is too computationally expensive to simulate proximity operations that involve thousands of thruster firings. For this analysis to be tractable, engineering models of the plume flowfield and impingement events are used to simulate these trajectories [1]. Currently, on-orbit plume impingement environments are modeled through an inefficient open-loop analysis cycle where the vehicle’s flight controller and plume impingement teams iterate on the trajectories until they pass the target vehicle’s plume requirements. As complex on-orbit missions evolve and become more frequent, lengthy design cycles will become operational bottlenecks. To address this gap, this work develops an advanced plume impingement module capable of operating at real-time scale that can be integrated with existing mission planning tools and onboard flight systems. The plume module leverages state-of-the-art plume simulation techniques [2] to deliver fast, physics-based impingement predictions in a software architecture that can be tailored to diverse proximity operations scenarios. A prototype of this plume impingement module is built to demonstrate the feasibility of real-time performance. This prototype completes plume impingement calculations in microseconds per target geometry mesh point. The software serves as a foundational capability for plume-aware trajectory design, operational risk assessment, and future autonomous decision-making systems.

Plume Impingement↗

NASA NTRS2017

Hyper-Spectral Networking Concept of Operations and Future Air Traffic Management Simulations

The NASA sponsored Hyper-Spectral Communications and Networking for Air Traffic Management (ATM) (HSCNA) project is conducting research to improve the operational efficiency of the future National Airspace System (NAS) through diverse and secure multi-band, multi-mode, and millimeter-wave (mmWave) wireless links. Worldwide growth of air transportation and the coming of unmanned aircraft systems (UAS) will increase air traffic density and complexity. Safe coordination of aircraft will require more capable technologies for communications, navigation, and surveillance (CNS). The HSCNA project will provide a foundation for technology and operational concepts to accommodate a significantly greater number of networked aircraft. This paper describes two of the HSCNA projects technical challenges. The first technical challenge is to develop a multi-band networking concept of operations (ConOps) for use in multiple phases of flight and all communication link types. This ConOps will integrate the advanced technologies explored by the HSCNA project and future operational concepts into a harmonized vision of future NAS communications and networking. The second technical challenge discussed is to conduct simulations of future ATM operations using multi-bandmulti-mode networking and technologies. Large-scale simulations will assess the impact, compared to todays system, of the new and integrated networks and technologies under future air traffic demand.

communication link modeling↗

NASA NTRS2023

Strategic Deconfliction of Small Unmanned Aircraft Using Operational Volume Blocks at Crossing Waypoints

In this research, first, analytical case studies are performed to understand the parameters on which the minimum temporal separation between unmanned aircraft at crossing waypoints is dependent for enabling strategic deconfliction. The analytical expressions show that the minimum temporal separation is a function of the length and width of operational volume blocks, the relative positions of the active operational volume blocks, groundspeed of unmanned aircraft, and the incoming crossing angle. Next, the parametric study shows that the impact of the incoming crossing angle on the minimum temporal separation at a crossing waypoint increases with an increase in the width of the operational volume blocks. Finally, simulation studies are performed to understand the impact of operational volume block sizing, on-demand departure rate, minimum departure time separation, and the incoming crossing angle on the average ground delay of unmanned aircraft traveling on two routes with a single crossing waypoint and identical on-demand departure rate. Each unmanned aircraft’s estimated time of arrival at a crossing waypoint is adjusted by introducing a ground delay in departure time; no other controls (e.g., speed adjustments) are applied for strategic deconfliction. Simulation studies show that the impact of the minimum temporal separation at a crossing waypoint on the average ground delay of flights is negligible if the minimum departure time separation is at least two times the minimum temporal separation. Therefore, with an increase in minimum departure time separation at a depot, the impact of increased length of operational volume blocks enclosing the crossing waypoint on the ground delay is offset to an extent.

Operational intent↗

NASA NTRS2023

Strategic Deconfliction of Small Unmanned Aircraft Using Operational Volume Blocks at Crossing Waypoints

Operational Intent↗