Multi-Vehicle Systems and Air Traffic Control Commons^™

Multimodal Interpretation Of Pilot–Controller Communications For Runway Safety Assurance And Enhanced Atc Situational Awareness., Chaebin Song, Juin Park

Discovery Day - Daytona Beach

Recent runway safety events have highlighted the importance of accurate and timely interpretation of pilot–controller communications, especially in complex airport environments where aircraft and ground vehicles interact on or near active movement areas. In light of the recent LaGuardia Airport collision, which has drawn attention to communication, coordination, and surface safety challenges, this project investigates how multimodal data can support air traffic controllers’ situational awareness and safety assurance. This study develops an in-progress framework that combines Automatic Speech Recognition (ASR) of pilot–controller radio communications with ADS-B trajectory data to improve interpretation of operational intent and cross-check communications against observed aircraft …

Improving Multi-Agent Swarm Collision Avoidance Using Reciprocal Velocity Obstacles, Nick Wilson

Discovery Day - Daytona Beach

As multi-agent systems grow increasingly complex, physical robotic swarms are essential to bridge the gap between limited software simulations and real-world application. The BID4R STARS swarm provides a physical platform for testing diverse algorithms, yet its success relies heavily on fundamental agent capabilities—most notably, obstacle avoidance. Preventing intra-swarm collisions is critical to avoid hardware damage and experimental disruption. To address this challenge, this project implements the Reciprocal Velocity Obstacles (RVO) algorithm onto the STARS swarm. While standard collision avoidance algorithms often overcorrect and induce oscillatory agent movement, RVO factors in the velocity and anticipated responses of all agents involved in …

Honeybee-Inspired Swarm Intelligence For Autonomous Adaptability Of Martian Infrastructure, Morgan Kendall

Discovery Day - Daytona Beach

Current research in autonomous space systems primarily relies on centralized control or swarm methods designed for fixed mission scenarios. These approaches lack the flexibility needed for long-duration Mars operations, where infrastructure must adapt to changing conditions, evolving mission goals, and limited human oversight. This creates a critical gap in developing autonomous systems capable of continuous self-organization. This gap is being addressed by developing a biologically inspired, adaptive Martian infrastructure using swarm intelligence. The scope includes key system domains such as power distribution, communication networks, and surface logistics. Agent-based modeling software will simulate infrastructure components as autonomous agents that evaluate local …

Applications Of A Swarm-Behavior Model On Existing Satellite Constellations, Naomi Lee

Discovery Day - Daytona Beach

The scope of this work explores biological swarm behavior and its application to low- and medium-sized Earth orbit satellite constellation systems. Existing constellation structures have predetermined orbits, meaning there is little adaptivity in the spacing and interactions between satellites. This allows for formation disruption by atmospheric perturbations in lower Earth orbit trajectories but can be countered with interactive controls that help with structure stability. This adaptive spacing and control can also be applied in MEO constellations in coverage and positioning optimization. In ‘mimicking’ this swarm behavior in starling murmurations, the separation, alignment, and cohesion flocking behavior of satellite groupings will …

Helio: Heliophysics Enhanced Learning For Intelligent Orbits, Kylie Nager, James Kirk

Discovery Day - Daytona Beach

HELIO: Heliophysics Enhanced Learning for Intelligent Orbits   Satellite constellations operating in near-Earth space are increasingly vulnerable to space weather disturbances, such as solar flares, coronal mass ejections (CMEs), and high-speed solar wind streams, which degrade communications, destabilize attitude control, and accelerate orbital decay. These disturbances directly threaten mission continuity, constellation availability, and space asset survivability. Current protective approaches rely primarily on ground-based alerts and lack integration with broader space domain awareness, which results in programmed reactive protocols that are often initiated too late to prevent performance degradation and asset loss. The HELIO project addresses this gap by turning space-weather forecasts …

Fault-Aware Flight Path Assessment For Evtols Using An Integrated Air Traffic Management Environment, John Clardy, Edison Alberto Martinez Samaniego

Discovery Day - Daytona Beach

This study introduces a simulation framework to evaluate Fault-Aware Flight Paths for electric vertical takeoff and landing (eVTOL) aircraft within an integrated air traffic management environment. By combining an air traffic management system with intelligent trajectory generation frameworks, the approach assesses the development of safe, adaptive, and fault-aware flight paths that account for traffic interactions, airspace features, and specific operational constraints. Real-world historical airspace traffic data was used to accurately simulate complex and congested operational conditions. The main goal is to evaluate the operational impact of integrating eVTOL operations into the National Airspace System, with a focus on conflict detection, …

Cars Imass - Comparing Llm Vs Human Operator Effectiveness In Multi-Agent Swarm Coordination, Gatlin Nelson

Discovery Day - Daytona Beach

Title: Dual-Perspective Risk Analysis for Human-LLM Decision Comparison in UAV Swarm Navigation   Unmanned aerial vehicle (UAV) swarms operating in low-altitude wireless network environments encounter localized disruptions that degrade positioning and navigation metrics. These disruptions are modeled as geographic failure zones with defined boundaries. A UAV discovers a zone by entering it and observing degraded performance on its onboard systems. This work assumes that affected UAVs can autonomously retreat to safety using onboard sensors and focuses on the subsequent rerouting decision. Once recovered, the system generates candidate repositioning points surrounding the vehicle, each scored using Conditional Value-at-Risk (CVaR). A human operator …

Phaëthon System, Brady Roudabush, Lauren Gallo, Emelia Thompson, Jacob Woods

Discovery Day - Daytona Beach

Phaëthon System is the project name for the Search and Rescue Drone Initiative. This initiative will improve the current search and rescue drone industry by introducing new techniques to get through dense forest canopies and other places where an overhead view is not useful. The Phaëthon System uses a swarm of drones that can penetrate under the tree canopy to map and search with the utmost efficiency and safety for rescuers. A command drone is launched to survey the overall search area, and set up a communications and data link. The next component is then released, which is a swarm …

Accelerating Search And Rescue Response: A Simulation Study On The Dynamic Efficiency Of Flocking-Enabled Drone Swarms, Sophia Beckwith, Carys Del Prete

Discovery Day - Daytona Beach

This project explores how imitations observed in animal group behavior, specifically flocking in birds, can be applied to the functionality of autonomous drone systems to aid in search and rescue efforts. The goal is to demonstrate how incorporating code based on the Boids, Vicsck and predictive control linear algebraic mathematical models for drone flight controls and the collective behaviors of flocks will increase the efficiency of drone maneuvers, allowing them to reorganize and fill gaps when one is removed. A MATLAB-based simulation was developed to model the behaviors using research conducted on the symmetric and synchronized behaviors observed from flocks …

Interplay Between Physical Design Choices And Emergent Cyber System Consensus: A Case Study With An Underwater Swarm, Ava Neubert

Discovery Day - Daytona Beach

Understanding how physical constraints influence collective behavior is critical for designing cyber-physical multi-agent systems in communication-limited environments. This project investigates how agent mobility and communication constraints affect opinion dynamics in a three-dimensional underwater swarm. An agent-based model was developed in AnyLogic, where agents follow realistic motion dynamics and exchange information at discrete communication intervals to reflect underwater limitations. Agent opinions are modeled using a BOIDS-inspired consensus mechanism in RGB space, allowing visualization of convergence behavior. A sensitivity analysis was conducted to evaluate the effects of communication range, agent speed, turn rate, and swarm size. Results show that communication range has …

Assessing Computer Vision Based Conflict Detection In Uas Traffic Monitoring Under Secure Communication Constraints, Fadjimata Issoufou Anaroua

Doctoral Dissertations and Master's Theses

The rapid growth of Unmanned Aircraft Systems (UAS) and Advanced Air Mobility (AAM) is creating a new low-altitude airspace ecosystem where drones, air taxis, service suppliers, communication networks, sensors, and ground-based monitoring systems must work together safely. Within this ecosystem, UAS Traffic Management (UTM) is expected to provide a digital framework for coordinating operations beyond traditional air traffic control. However, reliable integration also requires resilient monitoring methods that can detect non-cooperative aircraft, protect communication links, and maintain timely situational awareness under real-world constraints.

This dissertation examines how computer vision can support cooperative monitoring systems such as Remote ID and ADS-B …

Aircraft Turnaround Bottlenecks: Addressing Ground Handling Delays For Operational Excellence, Vigneswaran Cm, Syedeen Khan, Benedict M, Srinath R, Mukesh Pr, Jayaram R Pothnis, Inamul Hasan

International Journal of Aviation, Aeronautics, and Aerospace

Ground handling delays at major airports pose significant challenges, impacting operational efficiency, airline schedules, and passenger satisfaction. This study explores the root causes of these delays, including resource constraints, operational inefficiencies, adverse weather, technical failures, and security issues. By examining case studies from major airports, the report identifies key solutions such as technology integration, infrastructure upgrades, staff training, standardized procedures, and enhanced communication systems. The findings underscore the importance of adopting proactive and collaborative approaches to optimize ground handling operations, ensuring smoother airport workflows and improved service delivery in the face of growing air traffic demands.

Towards The Wearable Cardiorespiratory Sensors For Aerospace Applications, Chandan Sheikder

Journal of Aviation/Aerospace Education & Research

In safety-critical aviation operations, adaptive Human-Machine Interfaces (HMI) rely on accurate physiological monitoring to mitigate cognitive overload. While cardiorespiratory sensors are promising for real-time cognitive workload assessment, existing studies lack rigorous validation of consumer-grade devices in high-stress aviation contexts and fail to address measurement uncertainty propagation. This study evaluates the Zephyr BioHarness, a commercial wearable sensor, against clinical-grade equipment during arithmetic tasks simulating aviation cognitive demands. By integrating a neuro-fuzzy system with uncertainty propagation methods, we quantify the reliability of heart rate (HR) and breathing rate (BR) metrics for workload estimation. Results demonstrate moderate HR accuracy (RMSE: 4.85 bpm, CC: …

A New Trajectory In Uav Safety: Leveraging Reinforcement Learning For Distance Maintenance Under Wind Variations, Xiaolin Xu, Jeffrey Sun

Journal of Aviation/Aerospace Education & Research

In the field of aviation, safety is a critical cornerstone, and the operation of Unmanned Aerial Vehicle (UAV) systems is deeply connected with this principle. A thorough analysis and rigorous simulation and testing of aircraft systems are essential to avoid severe safety hazards. This paper delves into the safety issue in UAV operations, specifically regarding maintaining minimum safety distances under fluctuating wind conditions. The study introduces a novel solution based on a Deep Deterministic Policy Gradient (DDPG) model, a reinforcement learning method. The DDPG model was trained using a simulated environment created through the Gazebo simulator, with values for wind …

In-Flight Testing & Verification Of An Adaptive Distributed Fault-Tolerant Control Architecture, Michael Budihartono

Doctoral Dissertations and Master's Theses

The interest in utilizing multi-agent systems (MAS) has increased in the aerospace industry. Its scalability, efficiency, robustness, fault tolerance, and cost-effectiveness make it ideal for performing real-world missions that require more than one agent. However, in completing the tasks, the multi-agent systems are still vulnerable to environmental disturbances, cyber-attacks, and hardware failures. Therefore, an adaptive distributed fault-tolerant control architecture is needed to minimize the impacts of the previously stated circumstances and ensure the mission can continue successfully.

This thesis describes the development of an experimental setup for testing and validating an adaptive consensus algorithm and a bio-inspired health management architecture. …

Urban Air Mobility (Uam) Flight Path: Literature Review And Conceptual Design Of Uam Corridor Virtual Lane System Using “Tracks”, Immanuel Bankole

Student Works

As the Urban Air Mobility (UAM) industry grows and becomes more popular, most of the conversations in the public domain are focused on the (electric Vertical Take-off and Landing) eVTOL aircraft and the physical infrastructure that will support these eVTOL aircraft. However, there is a lack of research on UAM traffic management and flight paths taken by aircraft between locations.

The United States (U.S.) Federal Aviation Administration has proposed the use of corridors to minimize the interaction between UAM operations and traditional air traffic as eVTOL aircraft perform flight activities. The government also acknowledges the need for additional structures (such …

Stochastic Optimization To Reduce Aircraft Taxi-In Time At Igia, New Delhi, Rajib Das, Saileswar Ghosh, Rajendra Desai, Pijus Kanti Bhuin, Stuti Agarwal

International Journal of Aviation, Aeronautics, and Aerospace

Since there is an uncertainty in the arrival times of flights, pre-scheduled allocation of runways and stands and the subsequent first-come-first-served treatment results in a sub-optimal allocation of runways and stands, this is the prime reason for the unusual delays in taxi-in times at IGIA, New Delhi.

We simulated the arrival pattern of aircraft and utilized stochastic optimization to arrive at the best runway-stands allocation for a day. Optimization is done using a GRG Non-Linear algorithm in the Frontline Systems Analytic Solver platform. We applied this model to eight representative scenarios of two different days. Our results show that without …

A Deep Bilstm Machine Learning Method For Flight Delay Prediction Classification, Desmond B. Bisandu, Irene Moulitsas

Journal of Aviation/Aerospace Education & Research

This paper proposes a classification approach for flight delays using Bidirectional Long Short-Term Memory (BiLSTM) and Long Short-Term Memory (LSTM) models. Flight delays are a major issue in the airline industry, causing inconvenience to passengers and financial losses to airlines. The BiLSTM and LSTM models, powerful deep learning techniques, have shown promising results in a classification task. In this study, we collected a dataset from the United States (US) Bureau of Transportation Statistics (BTS) of flight on-time performance information and used it to train and test the BiLSTM and LSTM models. We set three criteria for selecting highly important features …

Ads-B Communication Interference In Air Traffic Management, George Ray

International Journal of Aviation, Aeronautics, and Aerospace

Automated Dependent Surveillance Broadcast (ADS-B) provides position and state information about aircraft and is becoming an essential component in the global air traffic management system. ADS-B transponders broadcast this key information on a common frequency to both other aircraft and to secondary surveillance radar systems located at ground stations. Both the aircraft transponders and the ground stations work together to assist in managing the commercial airspace. Since the aircraft transponders all broadcast on the same frequency and are in close proximity there is an apparent risk of interference and the garbling of the communications needed to manage the airspace.

The …

A Machine Learning Approach Towards Analyzing Impact Of Surface Weather On Expect Departure Clearance Times In Aviation, Dothag Truong, Shlok Misra, Godfrey V. D'Souza

Publications

Commercial air travel in the United States has grown significantly in the past decade. While the reasons for air traffic delays can vary, the weather is the largest cause of flight cancellations and delays in the United States. Air Traffic Control centers utilize Traffic Management Initiatives such as Ground Stops and Expect Departure Clearance Times (EDCT) to manage traffic into and out of affected airports. Airline dispatchers and pilots monitor EDCTs to adjust flight blocks and flight schedules to reduce the impact on the airline’s operating network. The use of time-series data mining can be used to assess and quantify …

Sme Coffee Hour: Human Factors: Dirty Dozennorms And Complacency, Linda Vee Weiland

Publications

Presentation about the relevance between communication, language, complacency and norms related to flight safety.

Air Navigation And Covid-19: Atm Efficiency In Pandemic Crisis, Fabio Lourenco Carneiro Barbosa

Graduate Student Works

The coronavirus crisis effects on aviation in 2020 are currently well-documented. Nonetheless, the widely registered low traffic due to the crisis does not necessarily lead to increased air navigation efficiency. Thus, the present work, developed to fulfill the program outcomes for the Master of Science in Aeronautics, Air Traffic Management (ATM) specialization, aimed to investigate what was the impact of the COVID-19 crisis on air navigation efficiency in Brazil. This research question was addressed through a quantitative, nonexperimental, observational approach with two parallel branches, designed to answer two sub-questions. For the first, regarding what was the impact of the crisis …

Air Traffic Controllers’ Occupational Stress And Performance In The Future Air Traffic Management, Hui Wang

Doctoral Dissertations and Master's Theses

As demand for unmanned aerial vehicle (UAV) operations increases, it is vital to understand its effects on air traffic controllers and the safety of the national airspace system. This study’s primary purpose is to determine how UAVs that operate in controlled airspace would influence air traffic controllers’ occupational stress and performance. In a within-subject experimental research design, 24 participants sampled from a university’s undergraduate Air Traffic Management (ATM) program completed three different air traffic control (ATC) scenarios on an en route ATC simulation system. The degree of UAV automation and control were varied in each scenario. The participants’ stress levels, …

Can The Timeframe Of Reported Uas Sightings Help Regulators?, Spencer Erik Pitcher, Kelly A. Whealan-George

Beyond: Undergraduate Research Journal

Remotely controlled small aircraft, otherwise known as Unmanned Aircraft Systems (UAS) or drones have started to impact the United States National Airspace System by interfering with the safe flight of aircraft. As the UAS industry continues its expected growth into the future, lawmakers, as well as regulators at the Federal Aviation Administration (FAA) and the aviation community must be able to predict when there will be more UAS craft in the air that could cause an interruption to air traffic so that more resources can be allocated optimally to counter the threat of UAS craft. The purpose of this study …

Methodology For Convergence Of The Training Program With The Professional Activities Of Aviation Specialists, Zair Ziyaevich Shamsiev

International Journal of Aviation, Aeronautics, and Aerospace

The method of developing curricula for training aviation specialists for civil aviation of the Republic of Uzbekistan is analyzed. It is substantiated that it does not sufficiently take into account the labor market requirements for the composition and content of academic disciplines. An overview of foreign experience in bridging the gap between educational programs and the workplace is given. A method based on a statistical analysis of civil aviation regulations is recommended.

Support To Design For Air Traffic Management: An Approach With Agent-Based Modelling And Evolutionary Search, Gabriella Gigante, Roberto Palumbo, Domenico Pascarella, Alessandro Pellegrini, Gabriella Duca, Miquel Angel Piera, Juan José Ramos

International Journal of Aviation, Aeronautics, and Aerospace

This paper presents a methodology to manage the support to design in ATM operations. We propose a workflow for the design of ATM solutions in a performance-based setting. The methodology includes the evaluation of the impact on human behaviour and exploits a combination of different paradigms, such as Agent-Based Modelling and Simulation, and Agent-Based Evolutionary Search. We prove the soundness of the methodology by carrying out a real case study, which is the transition from Direct Routing to Free Routing in the Italian airspace. The validation results exhibit limited errors for the assessment of the performance metrics under evaluation. Furthermore, …

Quantum Safety Metrics Framework For Commercial Unmanned Aircraft Operators, Tracy L. Lamb, Nathan A. Phillips, Trong Van Nguyen

International Journal of Aviation, Aeronautics, and Aerospace

Commercial unmanned aircraft systems continue to increase in applications and diversity; however, mishaps and accidents erode safety, investment return, and efficiency. Most unmanned aircraft accidents are preceded by leading indicators; the ability to forecast and quantify these may provide increased safety and profitability. This mixed-method research study used a non-experimental parallel convergence approach with multiple instruments, multiple-case study n = 22, and one exemplar case design to develop a quantum safety metric program. This study used a combination of previously validated methods as development instruments, including; the HFACS, STAMP, 'Sierra Scale,' and Accident Prevention Effort equations. The study extended the …

Predictability Improvement Of Scheduled Flights Departure Time Variation Using Supervised Machine Learning, Deepudev Sahadevan, Palanisamy Ponnusamy Dr, Manjunath K. Nelli Mr, Varun P. Gopi Dr

International Journal of Aviation, Aeronautics, and Aerospace

The departure time uncertainty exacerbates the inaccuracy of arrival time estimation and demand for arrival slots, particularly for movements to capacity constrained airports. The Estimated Take-Off Time (ETOT) or Estimated Departure Time(ETD) for each individual flight is currently derived from Air Traffic Flow Management System (ATFMS), which are solely determined based on individual flight plan Estimated Off Block Time(EOBT) or subsequent delays updated by Airline. Even if normal weather conditions prevail, aircraft departure times will differ from ETOTs determined by the ATFMS due to a number of factors such as congestion, early/delayed inbound flight (linked flights), reactionary delays and air …

Digitalization Of Educational And Methodological Support For The Training Of Aviation Dispatchers, Zair Ziyaevich Shamsiev

International Journal of Aviation, Aeronautics, and Aerospace

The tasks of improving the educational process of training civil aviation dispatchers on the basis of the development and implementation of digital teaching aids are considered. Legislative and regulatory documents are accepted as an object of digitalization. The end result of the research is expressed in the provision of the educational process with a special electronic educational complex, which has the functions of providing the necessary information and conducting practical exercises to deepen, consolidate and control knowledge in the field of aviation documents.

Sae Aero West Heavy Lift Competition Team - Eaglenautics, Anthony Pirone, Evan Stuart, Jessica Millard, Nathaniel Scott

Discovery Day - Prescott

ERAU’s SAE Aero Design West Competition team encourages students of all majors who have an interest in the design of heavy-lift cargo and passenger aircraft to design, build, and fly a large RC aircraft to meet a new set of regulations each competition year. Since the team, Eaglenautics, was founded in 2017 it has successfully been to competition once in April 2019 in California. The team’s aircraft flew 4 out of 5 flight rounds, passed all technical inspections, and is now on display in ERAU’s Aero-Fab in the AXFAB. The 2020 competition requirements are unique in that the cargo’s weight-to-volume …