Results for “Airspace Safety” — Page 6

NASA NTRS2020

Airspace Technology Demonstration 2 (ATD-2): Integrated Arrival/Departure/Surface (IADS) System Demonstration - Technology Transfer Document Summary (ReadMe) (Version 2.5 - Initial Phase 3 Metroplex IADS)

Airspace Technology Demonstration – 2 (ATD-2) is part of NASA’s Airspace Technology Demonstrations (ATD) Project under its Airspace Operations and Safety Program (AOSP). ATD-2 is a multi-year research and development effort to improve the predictability and operational efficiency of the air traffic system in metroplex environments while maintaining or improving throughput by enhancing and integrating arrival, departure, and surface prediction, scheduling, and management systems. In order to ensure that the products of this knowledge and technology transfer are relevant and useful, NASA has created strong partnerships with the FAA and industry stakeholders. This summary document and accompanying artifacts satisfy the next delivery of research transition products (RTPs) defined in the IADS research transition team (RTT) plan. With the ATD-2 project extended for another year, this Tech Transfer 2.5 constitutes an interim delivery of artifacts from the Phase 3 field demonstration. The final Phase 3 tech transfer delivery is planned for August 2021.

ATD-2, IADS, Phase 3, tech transfer↗

NASA NTRS2021

Airspace Technology Demonstration 2 (ATD-2): Integrated Arrival/ Departure/Surface (IADS) System Demonstration - Technology Transfer Document Summary (ReadMe)Version 3 (Final Phase 3 Metroplex IADS)

Airspace Technology Demonstration – 2 (ATD-2) is part of NASA’s Airspace Technology Demonstrations (ATD) Project under its Airspace Operations and Safety Program (AOSP). ATD-2 is a multi-year research and development effort to improve the predictability and operational efficiency of the air traffic system in metroplex environments while maintaining or improving throughput by enhancing and integrating arrival, departure, and surface prediction, scheduling, and management systems. In order to ensure that the products of this knowledge and technology transfer are relevant and useful, NASA has created strong partnerships with the FAA and industry stakeholders. This summary document and accompanying artifacts satisfy the final delivery of research transition products (RTPs) defined in the IADS research transition team (RTT) plan.

ATD-2↗

NASA NTRSDate not supplied

Advanced Capabilities for Emergency Response Operations (ACERO)

The Advanced Capabilities for Emergency Response Operations (ACERO) project is expected to develop, integrate, demonstrate, and transition to operations, evolving aviation technologies from NASA and industry to identify, monitor, and suppress wildland fires as a means to enhance safety, improve operational efficiency, and prevent economic loss. Some of the concepts ACERO explores are: wildfire airspace mangement to improve safety and resource utilization during a disaster, applying new aviation technologies to improve safety and demonstrate new mission-support capabilities, second-shift operations to enable progress towards 24/7 aerial response, and the integration of capabilities across NASA's Aeronautics Research, Science, and Space Technology mission directorates to enable expanded and scalable operations. Realizing this vision is expected to bring positive impact to such areas as: consistency of technology adoption through a unified concept of operations, airspace coordination and deconfliction that integrates portable solutions and enables diverse operations, remote sensing and data fusion for modeling and predictions that support in-time decision making, aircraft technologies for hazard avoidance and state management, and increased response capabilities through persistent communications and surveillance. ACERO continues the research begun under the Scalable Traffic Management for Emergency Response Operations (STEReO) activity, which brings together several technologies in Unmanned Aircraft Systems (UAS) Traffic Management (UTM), Autonomy, Communications, Human Factors, and Domain Expertise & Tools, aimed at providing scalability and flexibility, as well as operational resiliency to dynamic changes during a disaster event. Some of the concepts STEReO explores are: collaborative tools to ingest remote sensing information and distribute a common mission operating picture, apply ad-hoc communication networks to facilitate timely information sharing and communication of changes, vehicle-to-vehicle and onboard autonomy technologies ensure the safety and resiliency of operations, and apply NASA’s UAS traffic management system (UTM) as a public safety UAS Service Supplier (USS) to access and coordinate use of the airspace by both manned and unmanned operations. The potential benefits of STEReO include: standardized, cross-platform communication means increased interoperability and ease of cooperation/collaboration, increased situation awareness and common operating picture allow for earlier detection and decision making, and scalable to size and complexity of environment, operations, and mission objectives. This presentation gives an informational overview of the ACERO and STEReO projects to the Council of Western State Foresters (CWSF) Western State Fire Managers (WSFM) Committee.

emergency response operations↗

NASA NTRSDate not supplied

Enabling Smart Urban Airspaces through Distributed Sensing Technologies

Distributed sensing systems offer potential for enhancing safety and efficiency in urban airspaces and low-altitude metropolitan flight corridors. These systems leverage sensor networks to provide real-time airspace monitoring, situational awareness, and data for decision-making. This paper examines application of distributed sensing and smart airspace concepts to enable advanced urban flight, focusing on critical need applications such as airspace monitoring, corridor surveillance, precision navigation, and hazard avoidance. Benefits such as improved monitoring and increased situational awareness of activity within the urban airspace are considered alongside challenges in system design and implementation. This paper summarizes an ongoing effort to study the feasibility and effectiveness of distributed sensing systems for enabling urban airspace operations. Current research and design considerations are summarized, and a proposed roadmap for future work is presented.

Corey A Ippolito↗

NASA NTRS2019

In-Time Non-Participant Casualty Risk Assessment to Support Onboard Decision Making for Autonomous Unmanned Aircraft

Numerous operational paradigms, technologies, and missions are emerging as newcomers to the National Airspace System (NAS) develop small Unmanned Aircraft Systems (sUAS), personal air vehicles and other Urban Air Mobility (UAM) concepts. As the list of applications expands, maintaining the safety of the current airspace system remains one of the core concerns preventing widespread commercial implementation of these concepts. Further, the risks associated with unmanned aircraft operations themselves have to be recognized and mitigated in a timely manner. Safety-critical risks include, but are not limited to, flight outside of approved airspace, unsafe proximity to people or property, critical system failures, loss-of control, and cyber-security related risks. Instead of reacting to accidents, a set of predictive and data-driven risk monitoring, assessment, and mitigation capabilities are envisioned to help capture and eliminate hazards as these systems become operational. NASA’s System-wide Safety project is performing R&D on such a safety assurance concept. As part of this concept, this paper describes an architecture that continuously monitors a diverse set of onboard and ground-based sources to estimate and predict non-participant casualty risk during flight. Timely identification of the changing nature of this risk can inform decision making processes to mitigate current and impending situations.

Ancel, Ersin↗

NASA NTRSDate not supplied

The In-time Aviation Safety Management System Concept for Upper Class E Airspace

Explore the source record for details and available documents.

Kyle K Ellis↗

NASA NTRS2012

The National Aviation Operational Monitoring Service (NAOMS): A Documentation of the Development of a Survey Methodology

The National Aviation Operational Monitoring Service (NAOMS) was a research project under NASA s Aviation Safety Program during the years from 2000 to 2005. The purpose of this project was to develop a methodology for gaining reliable information on changes over time in the rates-of-occurrence of safety-related events as a means of assessing the safety of the national airspace. The approach was a scientifically designed survey of the operators of the aviation system concerning their safety-related experiences. This report presents the results of the methodology developed and a demonstration of the NAOMS concept through a survey of nearly 20,000 randomly selected air-carrier pilots. Results give evidence that the NAOMS methodology can provide a statistically sound basis for evaluating trends of incidents that could compromise safety. The approach and results are summarized in the report and supporting documentation and complete analyses of results are presented in 14 appendices.

Connors, Mary M.↗

NASA NTRS2006

Sense and Avoid Safety Analysis for Remotely Operated Unmanned Aircraft in the National Airspace System. Version 5

This document describes a method to demonstrate that a UAS, operating in the NAS, can avoid collisions with an equivalent level of safety compared to a manned aircraft. The method is based on the calculation of a collision probability for a UAS , the calculation of a collision probability for a base line manned aircraft, and the calculation of a risk ratio given by: Risk Ratio = P(collision_UAS)/P(collision_manned). A UAS will achieve an equivalent level of safety for collision risk if the Risk Ratio is less than or equal to one. Calculation of the probability of collision for UAS and manned aircraft is accomplished through event/fault trees.

Carreno, Victor↗

NASA NTRSDate not supplied

An In-time Aviation Safety Management System Concept of Operations and Modernization of the National Airspace System

The National Airspace System (NAS) is growing in complexity of aircraft, missions, and operations. In response, many organizations have published papers and concepts of operations (ConOps) for new and enhanced safety systems. The National Academies’ vision for an In-time Aviation Safety Management System (IASMS) is integral to Federal Aviation Administration (FAA) modernization efforts. The National Aeronautics and Space Administration (NASA) System-Wide Safety (SWS) project is conducting safety research, exploring solutions, and defining the safety needs of future missions, such as Advanced Air Mobility (AAM) and autonomous aircraft operating in a more connected, flexible, and dynamic airspace. IASMS enables and provides a path for bringing FAA’s operational vision to fruition through increasingly automated safety systems that integrate services, functions, and capabilities (SFCs). These SFCs provide the necessary responsiveness to monitor, assess, and mitigate known hazards and emergent risks. This paper describes how safety in today’s air transportation system will need to evolve, identifies key points regarding in-time safety, and explores the criticality of IASMS in the future NAS.

Airspace↗

NASA NTRSDate not supplied

An in-Time Aviation Safety Management System Concept of Operations and Modernization of the National Airspace System

The National Airspace System (NAS) is growing in complexity of aircraft, missions, and operations. In response, many organizations have published papers and concepts of operations (ConOps) for new and enhanced safety systems. The National Academies’ vision for an In-time Aviation Safety Management System (IASMS) is integral to Federal Aviation Administration (FAA) modernization efforts. The National Aeronautics and Space Administration (NASA) System-Wide Safety (SWS) project is conducting safety research, exploring solutions, and defining the safety needs of future missions, such as Advanced Air Mobility (AAM) and autonomous aircraft operating in a more connected, flexible, and dynamic airspace. IASMS enables and provides a path for bringing FAA’s operational vision to fruition through increasingly automated safety systems that integrate services, functions, and capabilities (SFCs). These SFCs provide the necessary responsiveness to monitor, assess, and mitigate known hazards and emergent risks. This paper describes how safety in today’s air transportation system will need to evolve, identifies key points regarding in-time safety, and explores the criticality of IASMS in the future NAS.

IASMS↗

NASA NTRSDate not supplied

An Approach to Identifying Aspects of Positive Pilot Behavior within the Aviation Safety Reporting System

The National Airspace System (NAS) is constantly evolving as air traffic continues to ramp up to pre-pandemic numbers and projected to grow to unprecedented levels in the coming years. As well as increasing demand to the current system, emerging operations such as Unmanned Autonomous Systems are also expected to add to complexity in the airspace. To address these issues, the industry and government agencies supporting the NAS will need to rely upon additional automation and new technologies to address future operational requirements, while continuing to be a world-leading safe transportation system. As these new technologies are implemented, the system continues to rely on human pilots and controllers in the loop to monitor the system and intervene in situations the automation cannot handle. The goal of proactively addressing safety is of foremost concern to ensure passenger confidence. The industry has implemented various Safety Monitoring Systems to identify safety risks and proactively address them before they result in a serious incident or accident. One such program is the Aviation Safety Reporting System (ASRS). ASRS is a long-established system where pilots and controllers voluntarily and anonymously report safety incidents they experienced and observed during line operations by providing rich text narratives describing the events, the environment, and conditions leading to the safety event of concern. These narratives provide insight and context around events of interest and can be used to identify emerging problems. They can trigger investigations within Flight Operational Quality Assurance or Flight Data Monitoring programs. However, this process typically focuses on the adverse events and the unsafe aspects of the operations surrounding the reported or detected events. This perspective of investigating factors that went wrong around an adverse event is commonly referred to as Safety I. Alternatively, characterizing successful actions that operators perform every day under varying conditions that keep the system within safe operating bounds is a concept referred to as Safety II. The benefit of the Safety II view is that the scope is much larger than that of Safety I since a vast majority of the operations result in successful flights. Many of the successful techniques used to manage operational threats are not documented in standard operating procedures or taught during training. They are typically acquired over time by working with experienced pilots during line operations or in many cases after experiencing a problem for the first time and reacting to it in situ, drawing from years of experience to manage the threat. In an attempt to quantify these positive actions, we are proposing an approach to extracting key behaviors within ASRS reports that can support the Safety II concept. Our analysis assumes that ASRS reports contain some descriptions of corrective actions that operators performed to prevent a situation from leading to an accident. Leveraging recent advances in Natural Language Process modeling, we have developed an approach to extract positive sentiment from reports, embed these positive statements in a vector space where they can be numerically analyzed, and clustering these statements into similar contextual categories. From these contextualized categories we can attempt to summarized and distilled aspects of the positive behavior. The goal is to identify categories of behavior that describe consistent operator techniques that supports the Safety II concept. With this information, airlines may enable learning from these positive actions, or address procedures that need to be changed to avoid having pilots implement a workaround. These insights can provide a lens into what is “going right” in the operations that may otherwise not be known widely within the community. It is envisioned that this approach can be extended to other narrative programs such as Line Operation Safety Audit or Learning Improvement Team reports where similar observed behavior can be analyzed to extract positive actions and inform the overall operations.

NLP↗

NASA NTRSDate not supplied

An Approach to Identifying Aspects of Positive Pilot Behavior within the Aviation Safety Reporting System

The National Airspace System (NAS) is constantly evolving as air traffic continues to ramp up to pre-pandemic numbers and projected to grow to unprecedented levels in the coming years. As well as increasing demand to the current system, emerging operations such as Unmanned Autonomous Systems are also expected to add to complexity in the airspace. To address these issues, the industry and government agencies supporting the NAS will need to rely upon additional automation and new technologies to address future operational requirements, while continuing to be a world-leading safe transportation system. As these new technologies are implemented, the system continues to rely on human pilots and controllers in the loop to monitor the system and intervene in situations the automation cannot handle. The goal of proactively addressing safety is of foremost concern to ensure passenger confidence. The industry has implemented various Safety Monitoring Systems to identify safety risks and proactively address them before they result in a serious incident or accident. One such program is the Aviation Safety Reporting System (ASRS). ASRS is a long-established system where pilots and controllers voluntarily and anonymously report safety incidents they experienced and observed during line operations by providing rich text narratives describing the events, the environment, and conditions leading to the safety event of concern. These narratives provide insight and context around events of interest and can be used to identify emerging problems. They can trigger investigations within Flight Operational Quality Assurance or Flight Data Monitoring programs. However, this process typically focuses on the adverse events and the unsafe aspects of the operations surrounding the reported or detected events. This perspective of investigating factors that went wrong around an adverse event is commonly referred to as Safety I. Alternatively, characterizing successful actions that operators perform every day under varying conditions that keep the system within safe operating bounds is a concept referred to as Safety II. The benefit of the Safety II view is that the scope is much larger than that of Safety I since a vast majority of the operations result in successful flights. Many of the successful techniques used to manage operational threats are not documented in standard operating procedures or taught during training. They are typically acquired over time by working with experienced pilots during line operations or in many cases after experiencing a problem for the first time and reacting to it in situ, drawing from years of experience to manage the threat. In an attempt to quantify these positive actions, we are proposing an approach to extracting key behaviors within ASRS reports that can support the Safety II concept. Our analysis assumes that ASRS reports contain some descriptions of corrective actions that operators performed to prevent a situation from leading to an accident. Leveraging recent advances in Natural Language Process modeling, we have developed an approach to extract positive sentiment from reports, embed these positive statements in a vector space where they can be numerically analyzed, and clustering these statements into similar contextual categories. From these contextualized categories we can attempt to summarized and distilled aspects of the positive behavior. The goal is to identify categories of behavior that describe consistent operator techniques that supports the Safety II concept. With this information, airlines may enable learning from these positive actions, or address procedures that need to be changed to avoid having pilots implement a workaround. These insights can provide a lens into what is “going right” in the operations that may otherwise not be known widely within the community. It is envisioned that this approach can be extended to other narrative programs such as Line Operation Safety Audit or Learning Improvement Team reports where similar observed behavior can be analyzed to extract positive actions and inform the overall operations.

NLP↗

NASA NTRSDate not supplied

An Approach to Identifying Aspects of Positive Pilot Behavior within the Aviation Safety Reporting System

The National Airspace System (NAS) is constantly evolving as air traffic continues to ramp up to pre-pandemic numbers and projected to grow to unprecedented levels in the coming years. As well as increasing demand to the current system, emerging operations such as Unmanned Autonomous Systems are also expected to add to complexity in the airspace. To address these issues, the industry and government agencies supporting the NAS will need to rely upon additional automation and new technologies to address future operational requirements, while continuing to be a world-leading safe transportation system. As these new technologies are implemented, the system continues to rely on human pilots and controllers in the loop to monitor the system and intervene in situations the automation cannot handle. The goal of proactively addressing safety is of foremost concern to ensure passenger confidence. The industry has implemented various Safety Monitoring Systems to identify safety risks and proactively address them before they result in a serious incident or accident. One such program is the Aviation Safety Reporting System (ASRS). ASRS is a long-established system where pilots and controllers voluntarily and anonymously report safety incidents they experienced and observed during line operations by providing rich text narratives describing the events, the environment, and conditions leading to the safety event of concern. These narratives provide insight and context around events of interest and can be used to identify emerging problems. They can trigger investigations within Flight Operational Quality Assurance or Flight Data Monitoring programs. However, this process typically focuses on the adverse events and the unsafe aspects of the operations surrounding the reported or detected events. This perspective of investigating factors that went wrong around an adverse event is commonly referred to as Safety I. Alternatively, characterizing successful actions that operators perform every day under varying conditions that keep the system within safe operating bounds is a concept referred to as Safety II. The benefit of the Safety II view is that the scope is much larger than that of Safety I since a vast majority of the operations result in successful flights. Many of the successful techniques used to manage operational threats are not documented in standard operating procedures or taught during training. They are typically acquired over time by working with experienced pilots during line operations or in many cases after experiencing a problem for the first time and reacting to it in situ, drawing from years of experience to manage the threat. In an attempt to quantify these positive actions, we are proposing an approach to extracting key behaviors within ASRS reports that can support the Safety II concept. Our analysis assumes that ASRS reports contain some descriptions of corrective actions that operators performed to prevent a situation from leading to an accident. Leveraging recent advances in Natural Language Process modeling, we have developed an approach to extract positive sentiment from reports, embed these positive statements in a vector space where they can be numerically analyzed, and clustering these statements into similar contextual categories. From these contextualized categories we can attempt to summarized and distilled aspects of the positive behavior. The goal is to identify categories of behavior that describe consistent operator techniques that supports the Safety II concept. With this information, airlines may enable learning from these positive actions, or address procedures that need to be changed to avoid having pilots implement a workaround. These insights can provide a lens into what is “going right” in the operations that may otherwise not be known widely within the community. It is envisioned that this approach can be extended to other narrative programs such as Line Operation Safety Audit or Learning Improvement Team reports where similar observed behavior can be analyzed to extract positive actions and inform the overall operations.

NLP↗

NASA NTRS2012

Aircraft Configuration and Flight Crew Compliance with Procedures While Conducting Flight Deck Based Interval Management (FIM) Operations

Flight deck based Interval Management (FIM) applications using ADS-B are being developed to improve both the safety and capacity of the National Airspace System (NAS). FIM is expected to improve the safety and efficiency of the NAS by giving pilots the technology and procedures to precisely achieve an interval behind the preceding aircraft by a specific point. Concurrently but independently, Optimized Profile Descents (OPD) are being developed to help reduce fuel consumption and noise, however, the range of speeds available when flying an OPD results in a decrease in the delivery precision of aircraft to the runway. This requires the addition of a spacing buffer between aircraft, reducing system throughput. FIM addresses this problem by providing pilots with speed guidance to achieve a precise interval behind another aircraft, even while flying optimized descents. The Interval Management with Spacing to Parallel Dependent Runways (IMSPiDR) human-in-the-loop experiment employed 24 commercial pilots to explore the use of FIM equipment to conduct spacing operations behind two aircraft arriving to parallel runways, while flying an OPD during high-density operations. This paper describes the impact of variations in pilot operations; in particular configuring the aircraft, their compliance with FIM operating procedures, and their response to changes of the FIM speed. An example of the displayed FIM speeds used incorrectly by a pilot is also discussed. Finally, this paper examines the relationship between achieving airline operational goals for individual aircraft and the need for ATC to deliver aircraft to the runway with greater precision. The results show that aircraft can fly an OPD and conduct FIM operations to dependent parallel runways, enabling operational goals to be achieved efficiently while maintaining system throughput.

Shay, Rick↗

NASA NTRS2024

Assessment of Some IASMS-relevant Data Sources for Aviation Safety

An In-time Aviation Safety Management System (IASMS) [1,2] is a set of services, functions, and capabilities (SFCs) necessary for monitoring known hazards and emergent risks, assessing safety data for anomalies, precursors, and trends, mitigating hazards that reach safety thresholds, and assuring efficacy of controls in mitigating hazards. An IASMS will continually monitor the NAS to collect data on the status of aircraft, air traffic management systems, weather, and airports. Within the NASA Aeronautics Research Mission Directorate (ARMD) System-Wide Safety (SWS) project’s technical challenge called In-time Aviation Safety Management Systems (IASMS) for Commercial Aviation Operations, which we often refer to as Technical Challenge 6 (TC-6), we have performed an assessment of several aviation data sources we have found that are relevant to assessing the safety of the National Airspace System (NAS) in the context of an IASMS. This assessment includes understanding the nature of the data themselves and using some data analytics tools on these data to show how they can be used to identify potential safety issues. We also describe how the data and analytics are part of a system that can allow for other data and analytics to be performed and for the results to be visualized for use by appropriate operators to identify potential safety issues and develop mitigations. This report is a step toward the ultimate goal of TC-6, which is to develop a prototype IASMS system that demonstrates the potential of an IASMS and inspire operators to build analogous systems to make the best possible use of the significant investments that they make in collecting, storing, and managingdata related to their operations.

aviation safety↗

NASA NTRS2012

Concepts of Integration for UAS Operations in the NAS

One of the major challenges facing the integration of Unmanned Aircraft Systems (UAS) in the National Airspace System (NAS) is the lack of an onboard pilot that can comply with the legal requirement identified in the US Code of Federal Regulations (CFR) that pilots see and avoid other aircraft. UAS will be expected to demonstrate the means to perform the function of see and avoid while preserving the safety level of the airspace and the efficiency of the air traffic system. This paper introduces a Sense and Avoid (SAA) concept for integration of UAS into the NAS that is currently being developed by the National Aeronautics and Space Administration (NASA) and identifies areas that require additional experimental evaluation to further inform various elements of the concept. The concept design rests on interoperability principles that take into account both the Air Traffic Control (ATC) environment as well as existing systems such as the Traffic Alert and Collision Avoidance System (TCAS). Specifically, the concept addresses the determination of well clear values that are large enough to avoid issuance of TCAS corrective Resolution Advisories, undue concern by pilots of proximate aircraft and issuance of controller traffic alerts. The concept also addresses appropriate declaration times for projected losses of well clear conditions and maneuvers to regain well clear separation.

Consiglio, Maria C.↗

NASA NTRSDate not supplied

Human Interfaces and Management of Information (HIMI) Challenges for “In-time” Aviation Safety Management Systems (IASMS)

The envisioned transformation of the National Airspace System to integrate an In-time Aviation Safety Management System(IASMS)to assure safety in Advanced Air Mobility(AAM)brings unprecedented challenges to the design of human interfaces and management of safety information. Safety in design and operational safety assurance are critical factors for how humans will interact with increasingly autonomous systems. The IASMS Concept of Operations builds from traditional commercial operator safety management and scales in complexity to AAM. The transformative changes in future aviation systems pose potential new critical safety risks with novel types of aircraft and other vehicles having different performance capabilities, flying in increasingly complex airspace, and using adaptive contingencies to manage normal and non-normal operations. These changes compel development of new and emerging capabilities that enable innovative ways for humans to interact with data and manage information. In-creasing complexity of AAM corresponds with use of predictive modeling, data analytics, machine learning, and artificial intelligence to effectively address known hazards and emergent risks. The roles of humans will dynamically evolve in increments with this technological and operational evolution. The interfaces for how humans will interact with increasingly complex and assured systems designed to operate autonomously and how information will need to be presented are important challenges to be resolved.

Lawrence J Prinzel↗

NASA NTRS2012

Development of Complexity Science and Technology Tools for NextGen Airspace Research and Applications

The objective of this research by NextGen AeroSciences, LLC is twofold: 1) to deliver an initial "toolbox" of algorithms, agent-based structures, and method descriptions for introducing trajectory agency as a methodology for simulating and analyzing airspace states, including bulk properties of large numbers of heterogeneous 4D aircraft trajectories in a test airspace -- while maintaining or increasing system safety; and 2) to use these tools in a test airspace to identify possible phase transition structure to predict when an airspace will approach the limits of its capacity. These 4D trajectories continuously replan their paths in the presence of noise and uncertainty while optimizing performance measures and performing conflict detection and resolution. In this approach, trajectories are represented as extended objects endowed with pseudopotential, maintaining time and fuel-efficient paths by bending just enough to accommodate separation while remaining inside of performance envelopes. This trajectory-centric approach differs from previous aircraft-centric distributed approaches to deconfliction. The results of this project are the following: 1) we delivered a toolbox of algorithms, agent-based structures and method descriptions as pseudocode; and 2) we corroborated the existence of phase transition structure in simulation with the addition of "early warning" detected prior to "full" airspace. This research suggests that airspace "fullness" can be anticipated and remedied before the airspace becomes unsafe.

Holmes, Bruce J.↗