Evaluation of Airport Size and Delay Causal Factor Effects on Delay Propagation Dissipation

The International Civil Aviation Organization identifies departure and arrival punctuality as on-time key performance indicators. However, these metrics assume a flight’s delay is a result of either the origin or destination airport, providing limited information on where delay should be mitigated in the U.S. National Airspace System (NAS). This study evaluates the relationship between delay propagation magnitude, delay causal factor, airport size, and charged facility (airport or Air Route Traffic Control Center), to examine if certain delays take longer to dissipate. First, using flights from July 2018, results show that most delay propagation chains originate at large-hub airports. However, these delays were the quickest to recover. Second, this study presents a regression model, predicting total propagated delay using fixed effects based on the weather region where the original delay occurred. Each additional flight affected by downstream delay adds 18.7 min on average to total arrival delay in a propagation chain. Additionally, if weather was the original causal factor, total propagated delay increased by 11.6 min compared with non-weather delays. Lastly, this study compares delay propagation in July 2018 and July 2020. Results show uneven impacts of the coronavirus disease 2019 (COVID-19) across the large-hub airports. Some of the investigated airports did not witness large improvements in average delay per delayed flight, warranting further research in the future. While delay and delay propagation have not been completely eradicated in the NAS during the COVID-19 pandemic, findings suggest that both have significantly declined on average.

Challenges and lessons learned introducing an evolving open source technology into an established legacy Ada and C++ program

When the Federal Aviation Administration (FAA) launched the System Wide Information Management (SWIM) initiative, the FAA had the goal of using the same portable, open infrastructure across all participating systems in the National Airspace System (NAS). Around 2008 for SWIM Segment 1, the FAA chose Iona Software's Free/Open Source Software (FOSS) based bundle, which was known and supported under the Fuse brand. The FAA obtained the licenses used by programs, including EnRoute Automation Modernization (ERAM), through Iona, which was later acquired by Progress and RedHat.

Exploratory Analysis of Unmanned Aircraft Sightings using Text Mining

Because of recent technological advancements, a growing number of unmanned aircraft systems (UASs) are anticipated to occupy the U.S. National Airspace System (NAS) and operate side-by-side with human pilot controlled civil aircraft. UAS technology has transitioned to broader applications, including commercial, scientific, and expanded military use. There have been significant challenges concerning the safe and suitable integration of UASs with existing systems. The interaction between humans and increasingly automated systems is of concern to researchers. Additionally, the number of UAS sightings has increased significantly during the last few years. In this study, the research team compiled 7,400 reports of UAS sightings (2015–2018). The Latent Dirichlet Allocation (LDA) method was then applied to develop topics relevant to UAS sighting incidents. This study also developed an online interactive tool to show keywords associated with different topics. These interactive topic models can help policymakers establish new policies and regulations to address specific safety concerns.

UAS Pilot Assessments of Display and Alerting for the Airborne Collision Avoidance System XU

Unmanned aircraft systems (UAS) must comply with specific standards to operate in the National Airspace System (NAS). Among the requirements are the detect and avoid (DAA) capabilities, which include display, alerting, and guidance specifications. Previous studies have queried pilots for their subjective feedback of these display elements on earlier systems; the present study sought pilot evaluations with an initial iteration of the unmanned variant of a Next Generation Airborne Collision Avoidance System (ACAS XU). Sixteen participants piloted simulated aircraft with both standalone and integrated DAA displays. Their opinions were gathered using post-block and post-simulation questionnaires as well as guided debriefs. The data showed pilots had better understanding and comfort with the system when using an integrated display. Pilots also rated ACAS XU alerting and guidance as generally acceptable and effective. Implications for further development of ACAS XU and DAA displays are discussed.