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Design and Implementation of a Scenario Development Process for a 2040 Trajectory-Based Operations Simulation

The National Aeronautics and Space Administration (NASA) is supporting research to transition from a legacy, air traffic management (ATM) system to Trajectory-Based Operations (TBO) environment targeting the 2035-2045 timeframe by creating simulation scenarios for current and future studies. TBO in the National Airspace System (NAS) focuses on modernizing the current operating paradigm to increase efficiency, predictability, resilience, and flexibility while migrating toward greater operational autonomy across the airspace. These simulation scenarios offer a wide dissemination and use of system-level constraints and aircraft state/intent data, routine use of data communications to request complex trajectory modifications and to receive clearances, and aircraft that are flying on 4-D trajectories with flexibility when desired, but structure where required. This report describes the end-to-end development of scenarios for the NASA Langley Research Center simulation environment to represent a 2040 Trajectory-Based Operations airspace for air transport operations research.

Trajectory-Based Operations↗

Effectiveness of Redundant Communications Systems in Maintaining Operational Control of Small Unmanned Aircraft

NASA has been researching prototype technologies for an Unmanned Aircraft System (UAS) Traffic Management (UTM) system to facilitate enabling of safe and efficient civilian low-altitude airspace and UAS operations, in a series of Technical Capability Levels (TCL) activities that are increasingly complex. In TCL1, completed in 2015, visual line-of-sight operations such as agriculture, firefighting and infrastructure monitoring were addressed with a focus on geofencing and operations scheduling. Technologies and requirements needed for beyond visual line-of-sight (BVLOS) operations in sparsely populated areas were examined in TCL2 in 2016, and those for operations over moderately populated areas in TCL3 in 2017 and 2018. TCL4 will build on the earlier TCLs and focus on technologies and requirements for operations in higher-density urban areas for tasks such as news gathering, package delivery and for managing large-scale contingencies. This paper describes a communications test conducted in TCL3 and discusses insights gained from the test. In the test, operators were directed to equip UAS with redundant Command and Control (C2) communications systems, send a maneuver command to Unmanned Aircraft (UA) via the primary system, then verify execution of the sent command. This exercise was repeated with each redundant system. The test was designed to assess effectiveness of redundant C2 systems in maintaining operational control of UA. Several UAS were configured with varying arrangements to achieve redundancy, including two identical radio modems using the same frequency band, WiFi and Long-Term Evolution (LTE) cellular modems, etc. From the test, digital data such as time maneuver command sent, time maneuver verified, etc., were collected. Descriptions of methods to detect loss of C2 communications and contingency steps for such event were collected and assessed. The final paper will include a detailed analysis of the collected data leading to the following insights. First, effectiveness of redundant C2 systems depends on several factors, such as operational environment and communications service availability. For example, use of two identical point-to-point radio to connect operator and UA on the same frequency band can be effective in mitigating radio malfunction when operating in an environment where possibility of Radio Frequency (RF) interference is low, such as over open plains. However, the same arrangement may not be effective where high level of RF transmissions in broad spectrum ranges can be expected, such as over or near urban areas. For redundant systems that consist of external communications services, such as cellular and satellite communications network, redundancy is maintained only in the areas where more than one services are available. Therefore, UAS operators should have the means to plan for and monitor the performance of external communications services they are relying on to control UA. Second, communications performance needs, such as the minimum data transfer rate and the maximum tolerable latency, should be assessed to reflect the potential hazard that can come from loss of UA control. For example, UA operations over desolate area pose less hazard to people than operations over densely populated area and performance need for the former would be less than the latter.

Jung, Jaewoo↗

Expanding the Use of Time-Based Metering: Multi-Center Traffic Management Advisor

Time-based metering is an efficient air traffic management alternative to the more common practice of distance-based metering (or "miles-in-trail spacing"). Despite having demonstrated significant operational benefit to airspace users and service providers, time-based metering is used in the United States for arrivals to just nine airports and is not used at all for non-arrival traffic flows. The Multi-Center Traffic Management Advisor promises to bring time-based metering into the mainstream of air traffic management techniques. Not constrained to operate solely on arrival traffic, Multi-Center Traffic Management Advisor is flexible enough to work in highly congested or heavily partitioned airspace for any and all traffic flows in a region. This broader and more general application of time-based metering is expected to bring the operational benefits of time-based metering to a much wider pool of beneficiaries than is possible with existing technology. It also promises to facilitate more collaborative traffic management on a regional basis. This paper focuses on the operational concept of the Multi-Center Traffic Management Advisor, touching also on its system architecture, field test results, and prospects for near-term deployment to the United States National Airspace System.

Landry, Steven J.↗

Preliminary Investigation of Impact of Technological Impairment on Trajectory-Based Operations

The Next Generation Air Transportation System (NextGen) incorporates collaborative air traffic management and Trajectory-Based Operations (TBO) in order to significantly increase the capacity, efficiency, and predictability of operations in the National Airspace System (NAS), without decreasing safety. This is enabled by airspace users and service providers sharing knowledge about operations that allows prediction of the complete 4D flight trajectory with as little uncertainty as possible. Additionally, new software and hardware technology is critical to reaching NextGen goals, especially with regard to TBO. What if the technologies that are critical for TBO were to be impaired or fail completely? Should there be a malfunction of a piece of the technology, it must be ensured that the whole system does not break down completely or suffer severe impairment. Instead, operations need to be maintained proportionally to the problem and safety needs to be ensured (graceful degradation). This paper proposes a systematic framework to investigate the vulnerability of TBO to technology disruption, and determine the impact of technological impairment on TBO. Two representative technologies are chosen for detailed investigation and the impact of their impairment on the degradation of TBO is illustrated using a weather-related scenario. XXXX There are several possible directions of future work. We believe it is desirable to develop methods to quantitatively assess the impact of technological disruption on TBO and to have the simulation tools to validate the impact. The availability of prognostics and health management methods could be leveraged to predict technological failure/disruption, thus predicting how TBO will be a ected, and possibly pro-actively mitigating the impact. It is important to develop large-scale scenarios where the e ect of technological impairment is prominent, and identify methods to quantitatively assess the extent of TBO degradation. An important goal of such an investigation is the development of failure-resistant resilient trajectory-based oper- ations. Resilience14, 15 is the property of a system to \bounce back" and resume at least a signi cant portion of its functionalities after degradation due to technological impairment(s). A systems resilience includes properties such as \bu ering capacity" (quantifying disruptions the system can absorb or adapt to without a fundamental breakdown in performance or in the systems structure), \ exibility" (ability to restructure itself in response to external changes or pressures), "margin" (how closely the system is currently operating rela- tive to one or another kind of performance boundary), \tolerance" (whether the system gracefully degrades as stress/pressure increase, or collapses quickly when pressure exceeds adaptive capacity), etc. Future work needs to focus on quantifying and improving the resilience of TBO, and identifying resilient design solutions for aviation.

TBO↗

Airport Information Sharing Concept Architecture

The National Airspace System (NAS) Air Traffic management, control and operation depends on a timely and efficient distribution of real time information generated by stakeholders and published from a variety of sources. The Federal Aviation Administration System Wide Information Management (SWIM) is a service oriented architecture design to provide stakeholders with timely NAS information. However, there are other sources of useful information generated by stakeholders that can be included in the management of NAS operations. Airport facilities are host to most stakeholders operating in the NAS (airspace user, airport authority, ground handling, controller tower) and thus large information is generated and consumed at these facilities. The NASA Glenn Research center has been investigating an information exchange architecture framework that would enable the timely, efficient and secure gathering and distribution information generated at airport facilities. This presentation describes the framework architecture concept for the efficient information exchange of airport information.

Airports↗

Evaluation of Initial and Midterm Air Traffic Procedures for Urban Air Mobility Operations

This paper describes a follow-on joint human-in-the loop (HITL) simulation effort by NASA and Joby Aviation that builds on the results of these previous studies. It extends that work by comparing the LOA condition for Initial UAM operations to Midterm operations that includes corridor airspace structures and some other changes to the operating environment. This is the first reported air traffic controller-in-the-loop evaluation of the corridor condition in a high-fidelity simulation environment. The following sections describe the routes, scenarios, and operating conditions along with metrics used to evaluate feasibility from the air traffic controllers’ perspectives. The results section presents the traffic levels that were feasible in each condition and concludes with recommendations for extending the scope and applicability of evaluations like this one in the future.

Savvy Verma↗

Demand Capacity Balancing at Vertiports for Initial Strategic Conflict Management of Urban Air Mobility Operations

Urban Air Mobility (UAM) is a new transportation concept that enables highly automated, cooperative, passenger or cargo-carrying air transportation services in and around urban areas. To achieve the high level of operational density and complexity desired by the UAM community, an airspace system that allows UAM operators to readily access and operate safely and efficiently in the airspace is needed. This airspace system will require air traffic management designed to reduce the risk of conflicts and loss of separation between UAM flights. In general, strategic conflict management is considered as the first layer of conflict management for safe flight operations to condition the traffic to reduce the need for airborne separation provision, the second layer of conflict management. Demand Capacity Balancing (DCB) is one of the concept components to achieve strategic conflict management. DCB strategically evaluates traffic demand and resource capacities to allow UAM operators to determine when, where and how they operate, while mitigating conflicting needs for airspace and vertiport capacity. DCB can be applied whenever UAM demand exceeds the capacity in airspace or at vertiports. As the UAM ecosystem evolves with advanced technologies and matured operational procedures, more complicated conflict management will likely be needed. In the current UAM ‘Concept of Operation (ConOps) 1.0’ operational stage defined by FAA, however, it will be meaningful to explore the demand capacity balancing at vertiports only, as an initial strategic conflict management approach for UAM operations because vertiport capacity seems to be a bottleneck of UAM traffic. For this research, we developed a demand-capacity imbalance detection and resolution service for UAM. This DCB service identifies the demand from operators and compares the demand to a given capacity at the shared resources (i.e., vertiports) over the upcoming time horizon which is divided into time bins having a constant interval. When a new flight plan is submitted, the algorithm embedded in the DCB service checks the available time bins based on the desired departure time and estimated arrival time at origin and destination vertiports, respectively. If the time bins for the originally desired times are already occupied by other flights (i.e., demand is at or above capacity), the algorithm finds the next available time bins for takeoff and landing and shifts the conflicting departure time to the earliest time that satisfies the capacity constraints at both origin and destination vertiports. The details of the algorithm will be described in the final manuscript. Figure 1 shows that the proposed DCB algorithm works well for a sample traffic scenario. In this example, a total of 144 flights, split between two operators, are planned over 2 hours, traveling 10 routes between five vertiports. In the heatmaps, the horizontal axis shows 12 time bins where each bin represents a 12-minute interval, and the vertical axis shows five vertiports. The number in each cell shows the number of operations, counting both departures and arrivals, at a specific vertiport in each time bin. For the given capacity of 2 operations/vertiport/bin, Figure 1 shows that the original demand sometimes exceeds the capacity, but the modified demand is reduced to the given capacity after resolving demand-capacity imbalances. When UAM flights are operated, it is expected that many practical issues would arise in the federated system architecture with multiple operators. UAM operators may experience a time synchronization issue due to communication delay between operator and vehicle. UAM vehicles would fly at different flight speeds, depending on vehicle models. Actual departure and arrival times can have large variations, compared to the schedule. The lead time from flight plan submission to desired departure time can vary by service type (e.g., regular shuttle service vs. on-demand service). Using the proposed DCB algorithm, we also investigated how the actual flight schedule and DCB performance are affected by these uncertainties such as unsynchronized times between operators, flight speed differences, lead time differences, and departure time errors. The final manuscript will include the background of this research work, the description of the DCB algorithm and its use cases with traffic scenarios. It will also provide the analytical results about the impact of various uncertainties that can occur in actual UAM operations on the DCB at vertiports, in terms of demand distribution changes, number of simultaneous operations, and delay propagation.

Urban Air Mobility↗

Upper Class E Traffic Management: NASA's Collaborative Research and Technical Development to Enable Routine, Safe, and Scalable High Altitude Operation

In the past, operations at high altitudes have been limited in number and largely conducted for defense/security purposes. However, with broad technological advances, a growing number of commerical and public good use cases, and a significant rise in the number of capable platforms, the demand for operating in high altitude airspace - known as upper Class E in the United States - is increasing. With that increase in demand comes the need for a means to manage the airspace in a way that does not burden current air traffic services and infrastructure given that provisions for commercial operations are limited. NASA, in collaboration with other government agencies and strong representation from industry, has developed a cooperative approach to airspace management referred to as Upper Class E Traffic Management (ETM). Key aspects of the ETM concept are the ability to exchange information through services that enable the operators to share airspace in cetain areas by adhering to cooperative operating practices (COPs) and by having shared situation awareness. To advance the concept, NASA recently developed and formally tested the first dedicated reference ETM system and supportin architecture. The test involved real-time simulation of high altitude operations with a diverse set of aircraft and encourter situations that included industry partners connected to the system from their remote operating centers. This presentation will provide attendees with an understanding of the ETM concept, the details and importance of the system that has been developed, an overview of the groundbreaking simulation, and a glimpse of things to come in our next steps.

Conrad Dang-Gabriel↗

ATM-X: Air Traffic Management – eXploration: Urban Air Mobility Overview

The UAM market is expected to be big in the billions of dollars. And, of course, UAM will need to be able to readily access and operate in the airspace for this to happen. In the ATM-X UAM sub-project, we are focused on NASA’s top-level goal of enabling UAM Maturity Level-4 (UML-4) operational density and complexity, with hundreds of simultaneous operations in a metropolitan area managed through a UTM-like architecture with third-party provided traffic management services. We are doing this by developing a concept of operations with the FAA and the UAM community that serves as a framework and guide for community research and development. We are also doing this by conducting research to define system requirements based on the concept and developing the UAM airspace management system for the AAM National Campaign.

urban air mobility↗

Identifying Common Use Cases across Extensible Traffic Management (xTM) for Interactions with Air Traffic Controllers

NASA’s Extensible Traffic Management (xTM) builds on the foundation and the architecture of Unmanned Aircraft Systems (UAS) Traffic Management (UTM) concept and extends it broadly to other domains, such as Advanced / Urban Air Mobility (AAM/UAM) and Upper Class E Traffic Management (ETM). These xTM concepts assume the ability to fly in airspace that is authorized to operate solely under xTM services and mostly without any air traffic control (ATC) support. However, they also assume circumstances in which the xTM vehicles would need to operate in conventional ATC-managed airspace, both during nominal and off-nominal scenarios. Due to the vast differences in the xTM vehicle performances and missions, there is a concern that ATC may have difficulty in safely managing the xTM traffic and providing appropriate services to all vehicles, unless a consistent set of roles, procedures, and data exchange requirements are defined across the diverse set of xTM vehicle operations. In this paper, we describe a set of use cases that have been identified in UTM, AAM/UAM, and ETM operations that are related to ATC interactions, and we propose to categorize these use cases across xTM domains based on common trigger events. Organizing the use cases from the perspective of ATC roles per each trigger event is expected to provide the first step in discovering common procedures and data requirements across xTM domains that could help ease the controllers’ cognitive task load and allow them to manage these interactions more safely.

Extensible Traffic Management (xTM)↗

Analysis of Aircraft Clusters to Measure Sector-Independent Airspace Congestion

The Distributed Air/Ground Traffic Management (DAG-TM) concept of operations* permits appropriately equipped aircraft to conduct Free Maneuvering operations. These independent aircraft have the freedom to optimize their trajectories in real time according to user preferences; however, they also take on the responsibility to separate themselves from other aircraft while conforming to any local Traffic Flow Management (TFM) constraints imposed by the air traffic service provider (ATSP). Examples of local-TFM constraints include temporal constraints such as a required time of arrival (RTA), as well as spatial constraints such as regions of convective weather, special use airspace, and congested airspace. Under current operations, congested airspace typically refers to a sector(s) that cannot accept additional aircraft due to controller workload limitations; hence Dynamic Density (a metric that is indicative of controller workload) can be used to quantify airspace congestion. However, for Free Maneuvering operations under DAG-TM, an additional metric is needed to quantify the airspace congestion problem from the perspective of independent aircraft. Such a metric would enable the ATSP to prevent independent aircraft from entering any local areas of congestion in which the flight deck based systems and procedures may not be able to ensure separation. This new metric, called Gaggle Density, offers the ATSP a mode of control to regulate normal operations and to ensure safety and stability during rare-normal or off-normal situations (e.g., system failures). It may be difficult to certify Free Maneuvering systems for unrestricted operations, but it may be easier to certify systems and procedures for specified levels of Gaggle Density that could be monitored by the ATSP, and maintained through relatively minor flow-rate (RTA type) restrictions. Since flight deck based separation assurance is airspace independent, the challenge is to measure congestion independent of sector boundaries. Figure 1 , reproduced from Ref. 1, depicts an example traffic situation. When the situation is analyzed by sector boundaries (left side of figure), a Dynamic Density metric would identify excessive congestion in the central sector. When the same traffic situation is analyzed independent of sector boundaries (right side of figure), a Gaggle Density metric would identify congestion in two dynamically defined areas covering portions of several sectors. The first step towards measuring airspace-independent congestion is to identify aircraft clusters, i.e., groups of closely spaced aircraft. The objective of this work is to develop techniques to detect and classify clusters of aircraft.

Bilimoria, Karl D.↗

A Consideration of Constraints on Aircraft Departure Operations

This paper presents a system-level perspective on the operational issues and constraints that limit departure capacity at large metropolitan airports in today's air transportation system. It examines the influence of constraints evident in en route airspace, in metroplex operations, and at individual airports from today's perspective and with a view toward future gate-to-cruise operations. Cross cutting organizational and technological challenges are discussed in relation to their importance in addressing the constraints.

Darr, Stephen T.↗

Dynamic Airspace Configuration

In air traffic management systems, airspace is partitioned into regions in part to distribute the tasks associated with managing air traffic among different systems and people. These regions, as well as the systems and people allocated to each, are changed dynamically so that air traffic can be safely and efficiently managed. It is expected that new air traffic control systems will enable greater flexibility in how airspace is partitioned and how resources are allocated to airspace regions. In this talk, I will begin by providing an overview of some previous work and open questions in Dynamic Airspace Configuration research, which is concerned with how to partition airspace and assign resources to regions of airspace. For example, I will introduce airspace partitioning algorithms based on clustering, integer programming optimization, and computational geometry. I will conclude by discussing the development of a tablet-based tool that is intended to help air traffic controller supervisors configure airspace and controllers in current operations.

airspace↗

Application of AI in the NAS - the Rationale for AI-Enhanced Airspace Management

This paper extends on the initial findings of "Application of Artificial Intelligence in the National Airspace System: A Primer" (Stroup & Niewoehner: Herndon, VA; ICNS-2019), and looks at why the current technologies, enterprise architecture, and future program plans may not be enough to address persistent operational challenges. This paper further explores why emergent operational concepts, business models, and demand profiles may necessitate AI-enhanced Communications, Navigation and Communications (CNS) infrastructure to disrupt current operational impediments. European airspace, as well as the NAS, has similar challenges. Key challenges explored in this study include: quantifiable improvements to NAS capacity, efficiency, and resiliency; traffic flow management of diverse users; UTM-ATM airspace integration; equitable access to airspace; and airborne-ground interoperability of AI applications. Finally, we examine why trustworthiness and resiliency will be key mileposts on the regulatory pathway to AI certification.

Aviation↗

An Exploratory Evaluation of UAS Detect and Avoid Operations in the Terminal Environment

New technical standards for Unmanned Aircraft Systems (UAS) detect and avoid (DAA) systems mark recent progress toward realizing the goal of full integration of UAS into the National Airspace System (NAS). The DAA system is intended to provide a means of compliance with operating regulations that required pilots on board manned aircraft to remain "well clear" of other aircraft which is accomplished through out-the-window visual acquisition of other aircraft and application of a subjective judgment of safe separation. The requirements for the DAA system, including the specification of a DAA well clear threshold as well as functional requirements for detecting, tracking, alerting and guidance processing, and displays, are specified in DO-365, Minimum Operational Performance Standards (MOPS) for DAA Systems developed within RTCA Special Committee 228 (SC-228). Intended as the first in a series of phased versions, these requirements are frequently referred to as the "Phase 1" DAA system. The Phase 1 DAA system is limited for use by aircraft transitioning to and from Class A or special use airspace, through Class D, E, and G airspace. In particular, the Phase 1 DAA MOPS are not intended for terminal airspace operations, a critical gap for enabling a full range of UAS operations. The application of the Phase 1 DAA system and DAA well clear threshold within the terminal area is predicted to result in a high number of unnecessary alerts when the UAS is safely separated from other traffic. The goal of the present study was to examine pilot performance and operational issues related to the operation of the Phase 1 DAA system in a terminal area. This experiment was intended as an exploratory study that would be used to inform the development of a new terminal area-specific DAA well clear definition, and associated alerting and guidance requirements. The two main objectives of this study were to: 1) characterize pilot behavior in the terminal environment with the Phase 1 DAA system, and 2) investigate the effect of modifications to the Phase 1 DAA alerting and guidance structure. In particular, the authors were interested in determining whether the removal of specific alerting and guidance levels, without changing the DAA well clear definition or alerting thresholds, would impact pilot performance while conducting terminal operations. The results indicate that the Phase 1 well clear definition and alerting and guidance resulted in frequent alerting that degraded pilots' ability to discriminate between encounters where another aircraft was safely separated versus when a maneuver was necessary. The resulting impact on pilot performance was slower response times and higher frequency and severity of losses of DAA well clear compared to those observed for experiments examining pilot performance in the en route environment. There was no significant effect of alerting and guidance display configuration on pilot performance.

Rorie, Conrad↗

An Exploratory Evaluation of UAS Detect and Avoid Operations in the Terminal Environment

New technical standards for Unmanned Aircraft Systems (UAS) detect and avoid (DAA) systems mark recent progress toward realizing the goal of full integration of UAS into the National Airspace System (NAS). The DAA system is intended to provide a means of compliance with operating regulations that required pilots on board manned aircraft to remain "well clear" of other aircraft which is accomplished through out-the-window visual acquisition of other aircraft and application of a subjective judgment of safe separation. The requirements for the DAA system, including the specification of a DAA well clear threshold as well as functional requirements for detecting, tracking, alerting and guidance processing, and displays, are specified in DO-365, Minimum Operational Performance Standards (MOPS) for DAA Systems developed within RTCA (Radio Technical Commission for Aeronautics) Special Committee 228 (SC-228). Intended as the first in a series of phased versions, these requirements are frequently referred to as the "Phase 1" DAA system. The Phase 1 DAA system is limited for use by aircraft transitioning to and from Class A or special use airspace, through Class D, E, and G airspace. In particular, the Phase 1 DAA MOPS are not intended for terminal airspace operations, a critical gap for enabling a full range of UAS operations. The application of the Phase 1 DAA system and DAA well clear threshold within the terminal area is predicted to result in a high number of unnecessary alerts when the UAS is safely separated from other traffic. The goal of the present study was to examine pilot performance and operational issues related to the operation of the Phase 1 DAA system in a terminal area. This experiment was intended as an exploratory study that would be used to inform the development of a new terminal area-specific DAA well clear definition, and associated alerting and guidance requirements. The two main objectives of this study were to: 1) characterize pilot behavior in the terminal environment with the Phase 1 DAA system, and 2) investigate the effect of modifications to the Phase 1 DAA alerting and guidance structure. In particular, the authors were interested in determining whether the removal of specific alerting and guidance levels, without changing the DAA well clear definition or alerting thresholds, would impact pilot performance while conducting terminal operations. The results indicate that the Phase 1 well clear definition and alerting and guidance resulted in frequent alerting that degraded pilots' ability to discriminate between encounters where another aircraft was safely separated versus when a maneuver was necessary. The resulting impact on pilot performance was slower response times and higher frequency and severity of losses of DAA well clear compared to those observed for experiments examining pilot performance in the en route environment. There was no significant effect of alerting and guidance display configuration on pilot performance.

terminal area↗

Operational Integration Potential of Regional Uncrewed Aircraft Systems Into the Airspace System

As part of newly developing aviation markets, fixed-wing Uncrewed Aircraft Systems (UAS) are projected to impact airspace systems and conventional air traffic in the future. The initial introduction of fixed-wing cargo UAS for regional operations is anticipated to occur at smaller under-utilized airports. Therefore, this paper assesses the integration potential of regional fixed-wing cargo UAS into the airspace system. A baseline is established to identify potential airports for cargo UAS operations in different areas. Additionally, using 2022 data, regional aircraft eligible for future cargo UAS operations are investigated. Finally, the accessibility of these regional aircraft at the identified airports was analysed. Based on the availability of current certified landing systems needed for initial UAS operations, potential airports in the areas Germany, Texas, and California for UAS operations are compared. Additionally, based on the maximum takeoff weight allowances of airport runways, current air transport operations at airports, and airspace classes, individual airports with a high potential for the introduction of initial cargo UAS operations with and without the availability of landing systems needed for UAS are identified and compared among the investigated areas. Despite a total of 173 identified airports for potential UAS operations in Germany, 376 in Texas, and 231 in California, only eleven of these airports currently have the certified landing systems needed for initial UAS operations. However, other landing system technologies that are currently under development, such as vision-based landing systems, might support UAS accessibility at the identified airports for potential UAS operations in the future.

Uncrewed aircraft systems↗

Validating the Airspace Concept Evaluation System for Different Weather Days

This paper extends the process for validating the Airspace Concept Evaluation System using real-world historical flight operational data. System inputs such as flight plans and airport en-route capacities, are generated and processed to create a realistic reproduction of a single day's operations within the National Airspace System. System outputs such as airport throughput, delays, and en-route sector loads are then compared to real world operational metrics and delay statistics for the reproduced day. The process is repeated for 4 historical days with high and low traffic volume and delay attributed to weather. These 4 days are simulated using default en-route capacities and variable en-route capacities used to emulate weather. The validation results show that default enroute capacity simulations are closer to real-world data for low weather days than high weather days. The use of reduced variable enroute capacities adds a large delay bias to ACES but delay trends between weather days are better represented.

Zelinski, Shannon↗