Air Traffic Management and Optimization

Neueste Paper

• Offline Multimodal Large Language Models for Decision Support in Air Operations

  Joao P. A. Dantas, Jelton A. Cunha, Gabriel Dietzsch · 21. September 2026

  Air operations rely on complex rules, established procedures, and time-critical analysis under limited connectivity and strict security constraints. In such environments, analysts must combine written doctrine with images, often without access to external computing resources. This paper studies offl…

• AURORA: A Natural Language-Driven Agentic Framework for Understanding, Reasoning, and Orchestrating Reliable Air-Ground Co-Simulation

  Keshu Wu, Hao Zhang, Rui Gan, Xiangbo Gao, Xiaopeng Li, Zhengzhong Tu, Yang Zhou · 18. September 2026

  Air-ground transportation research increasingly relies on co-simulation, yet constructing scenarios remains labor-intensive and difficult to validate. More importantly, a generated scenario may execute successfully while failing to realize the spatial, temporal, communication, or behavioral relation…

• FlowATC: Aircraft Trajectory Prediction via Flow Matching

  Mathurin Petit, Emir Torun, Louis Brusset, Jordan Kam, Alexandre M. Bayen · 16. September 2026

  Building accurate decision-support tools for next-generation air traffic control requires robust trajectory prediction models. We present a flow-matching architecture trained exclusively on historical aircraft trajectories, with no route labels or chart supervision. Trained on 1.15 million Automatic…

• Toward a Decision-Assurance Layer for AI-Assisted Flight Planning in Air Traffic Management

  Alexandre Barreto (George Mason University), Shou Matsumoto (George Mason University), Jorge Valverde-Rebaza (Tecnol\'ogico de Monterrey), Cleiton Ataide (DECEA: Department of Airspace Control), Paulo Costa (George Mason University) · 15. September 2026

  Generative AI is increasingly being used informally in Air Traffic Management (ATM) for tasks such as flight plan generation, trajectory interpretation, and constraint checking. Although these tools can reduce workload and accelerate planning, their non-deterministic outputs create safety and operat…

• V2TATC: Joint Voice-Trajectory Embedding and Dataset for Air Traffic Controller Situational Awareness

  Louis Brusset, Mathurin Petit, Jordan Kam, Alexandre Bayen · 10. September 2026

  As air traffic volumes in the National Airspace System continue to expand, in particular at low altitude, the need for scalable decision support tools used by air traffic controllers will also require more development. This article introduces Voice-to-Trajectory for Air Traffic Control, a joint voic…

• Formal, Executable and Explainable Runtime Monitoring of Spoken Air Traffic Control Operational Procedures

  Roberto Luvini, Giacomo Longo, Alessandro Armando, Enrico Russo · 27. August 2026

  Air traffic control procedures are executed through spoken exchanges between controllers and pilots. These interactions are essential to the safety of air transportation: failures in their execution can create severe operational hazards, as evidenced by past fatal accidents. Assessing whether an ins…

• Towards On-Board Implementation of ML-Based Helicopter Weight Estimator

  Nicolas Valot, Ammar Mechouche, Benjamin Lesage, Claire Pagetti, Louis Fabre · 21. August 2026

  This paper focuses on the implementation of a novel supervised Machine Learning model for estimating helicopter weight during takeoff, utilizing extensive datasets from Airbus's global in-service fleet. The study details a learning assurance process aligned with the EASA concept paper for machine le…

• AeroCopilotBench: A Two-Tier Benchmark for Evaluating LLM Agents as Aviation Copilots in an Interactive Virtual Cockpit Environment

  Yuchen Yuan, Zhenghuang Wu, Yuangan Li, Liang Ma, Ke Li · 18. August 2026

  Large language model (LLM) agents may assist flight crews with complex decisions and task execution, but existing aviation evaluations centered on static knowledge do not support systematic testing of procedural execution and safety compliance in interactive environments. This paper presents the Aer…

• Advanced modelling and data analytics in aviation

  Aziida Nanyonga · 18. August 2026

  The aviation industry characterized by its stringent safety standards has seen a growing need for innovative approaches to enhance safety measures. Despite the vast accumulation of aviation safety data over time, its full potential in predicting and preventing incidents has not been fully realized. …

• Can Vision Models Read the Radar Display? On the Feasibility of Radar Imagery for Air Traffic Complexity Estimation

  Hyewook Kim, Byul Kang, Seokbin Yoon, Keumjin Lee · 13. August 2026

  Air traffic controllers perceive traffic complexity through the radar display, suggesting that a computer vision model operating on the same imagery may provide a natural architecture for modeling controller-perceived complexity; however, whether radar imagery is a viable input format for deep learn…

• TailBooster: A Dual-Layer Generative Framework for Extreme Value Augmentation with Operational Validity Enforcement

  Karim Aly, Alexei Sharpanskykh, Jacco Hoekstra · 13. August 2026

  Extreme events in air transport, such as severe arrival delays and abnormal air times, cause cascading network disruptions with substantial operational, economic, and safety costs. Such events are rare in historical records, leaving insufficient training signal for machine learning models. Synthetic…

• ASPaeroFlow: Decomposition Heuristics for Joint Air Traffic Flow & Capacity Management

  Alexander Beiser, Markus Hecher, Nysret Musliu, Georg Trausmuth, Stefan Woltran · 11. August 2026

  While mathematical models act as vital decision support systems for operational Air Traffic Flow and Capacity Management (ATFCM), existing approaches isolate Air Traffic Flow Management (ATFM) from Dynamic Airspace Configuration (DAC). This separation introduces an unresolved circular dependency bet…

• A QUBO-Inspired Computational Framework for Airport Landside Bottleneck Diagnosis and Dynamic Dispatch Optimization

  Wuming Lei, Xiaobin Li, Mingyan Sun, Jianing Long, Yulin Tong, Yanbin Gao · 11. August 2026

  Airport landside traffic centers connect terminal arrivals with taxis, ride-hailing vehicles, private cars, buses, metro services, parking facilities, and terminal-area roadways. Peak arrivals can create coupled congestion across passenger queues, vehicle queues, pickup berths, storage areas, and ac…

• Integrated Noise and Safety Management in UAM via A Unified Reinforcement Learning Framework

  Surya Murthy, Zhenyu Gao, John-Paul Clarke, Ufuk Topcu · 6. August 2026

  Urban Air Mobility (UAM) envisions the widespread use of small aerial vehicles to transform transportation in dense urban environments. However, UAM faces critical operational challenges, particularly the balance between minimizing noise exposure and maintaining safe separation in low-altitude urban…

• From Keypoints to Predictive Distributions: Post-Hoc Uncertainty for YOLO-Pose Models

  Alexej Klushyn, Juan Rivero Sesma, Florian Seligmann, Richard Kurle, Kinh Tieu, Jayant Sen Gupta · 30. Juli 2026

  YOLO-Pose models provide efficient keypoint localization, but do not quantify the associated spatial uncertainty. We introduce a lightweight post-hoc probabilistic extension that augments a trained YOLO-Pose model with calibrated bivariate predictive distributions over keypoint locations, centered a…

• Explainable Reinforcement Learning for assisting Air Traffic Controllers

  Anduel Mehmeti, Gabriella Gigante, Salvatore Venticinque · 27. Juli 2026

  To effectively integrate AI into high-stakes, critical environments such as healthcare, autonomous driving, and aviation--and to advance toward higher levels of automation and seamless human-AI collaboration--building trust in AI-driven solutions is essential. Trust, in turn, is closely linked to th…

• Conflict Resolution under Degraded Surveillance in Air Corridors Using Multi-Agent Reinforcement Learning

  Esrat Farhana Dulia, Syed Arbab Mohd Shihab, Caleb Adams, Ruben Del Rosario · 24. Juli 2026

  Safe Advanced Air Mobility operations require aircraft to maintain separation when surveillance information is noisy, delayed, incomplete, or temporarily unavailable. This study develops a Deep Q-Network-based Multi-Agent Reinforcement Learning framework for decentralized conflict resolution among h…

• Declarative Problem Solving in UAM Strategic Deconfliction

  Gioacchino Sterlicchio (DMMM, Polytechnic University of Bari, Bari, Italy), Angelo Oddi (ISTC-CNR, Rome, Italy), Riccardo Rasconi (ISTC-CNR, Rome, Italy), Francesca Alessandra Lisi (DIB,CILA, University of Bari Aldo Moro, Bari, Italy) · 24. Juli 2026

  The growing demand for Urban Air Mobility (UAM) introduces significant challenges in airspace management, particularly within densely populated metropolitan regions. As the number of aerial vehicles-such as drones, air taxis, and helicopters-continues to rise, so does the risk of mid-air collisions …

• Runtime Safety Filtering for Learned Small UAS Separation Policies under GNSS Degradation

  Alex Zongo, Peng Wei · 14. Juli 2026

  Learning-based separation assurance for small Unmanned Aircraft Systems (sUAS) achieves near-zero collision rates in simulation, but assumes accurate position and velocity information from Global Navigation Satellite Systems (GNSS). This assumption fails in urban environments, where multipath propag…

• Pre-Flight: A Benchmark for Evaluating Large Language Models on Aviation Operational Knowledge

  Alex Brooker, Tim Hughes · 3. Juli 2026

  Large language models (LLMs) are increasingly proposed for aviation business operations, from documentation and training generation to customer facing assistants. General purpose benchmarks do not measure whether a model reasons safely and correctly about aviation specific operational knowledge, and…

• Solution space path planning for supporting en-route air traffic control

  Yiyuan Zou, Wenying Lyu, Clark Borst · 2. Juli 2026

  As technology advances, many path-planning algorithms have been proposed for Air Traffic Management, yet their operational adoption in tactical control remains limited, revealing a misalignment between algorithmic design priorities and air traffic controllers' needs. This underscores the need for de…

• Decentralized Coordination of Autonomous Traffic Through Advanced Air Mobility Corridors

  Jasmine Jerry Aloor, Hamsa Balakrishnan · 24. Juni 2026

  The use of dedicated corridors for Advanced Air Mobility (AAM) traffic is one of the most commonly proposed pathways to integrating them into existing airspace operations. Most prior research has focused on the design of networks of AAM corridors and conflict resolution for aircraft within corridors…

• Decentralized Autonomous Traffic Management through Corridor Networks

  Jasmine Jerry Aloor, Aadarsh Govada, Hamsa Balakrishnan · 23. Juni 2026

  As autonomous aircraft are introduced at scale and traffic density increases, centralized management becomes insufficient to coordinate the large numbers of crewed and uncrewed aircraft. Dedicated Advanced Air Mobility (AAM) corridors have therefore been proposed for organizing high-density autonomo…

• Joint Air Traffic Flow and Capacity Management via Answer Set Programming

  Alexander Beiser, Markus Hecher, Nysret Musliu, Stefan Woltran · 23. Juni 2026

  Operational Air Traffic Flow and Capacity Management (ATFCM) balances flight demand with available sector capacity, to ensure safe and efficient operations. Mathematical models enhance operational ATFCM performance by framing demand-capacity balancing as an optimization problem, maximizing efficienc…

• From Sentiment to Actionable Insights: Public Sentiment Analysis of Advanced Air Mobility

  Esrat Farhana Dulia, Amina Dhaher, Raiful Hasan, Syed Arbab Mohd Shihab · 19. Juni 2026

  Advanced Air Mobility (AAM) is an emerging low-altitude transportation system whose successful deployment depends on both technological progress and public acceptance. Public acceptance can influence government support, regulations, noise standards, willingness to fly, and the commercial viability o…