Build 8 of the Airspace Concept Evaluation System

George, Sapa; Satapathy, Goutam; Manikonda, Vikram; Palopo, Kee; Meyn, Larry A.; Lauderdale, Todd A.; Downs, Michael; Refai, Mohamad; Dupee, Richard

doi:10.2514/6.2011-6373

Cited by 48 publications

(26 citation statements)

References 10 publications

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“…The adaptive weight algorithm was prototyped in fast-time simulations using ACES [17]. ACES is a fast-time, gate-to-gate simulation and modeling tool of the National Airspace System that creates trajectories for aircraft using aircraft performance models derived from the Base of Aircraft Data [22].…”

Section: Establishing Proof-of-concept Throughmentioning

confidence: 99%

“…Following that is a section with a detailed derivation and description of the adaptive weight algorithm starting from a simplified form of the point-mass aircraft equations of motion [16]. The section after that contains the results of fast-time simulations using the Airspace Concept Evaluation System (ACES) [17] that establish proof-of-concept for the algorithm. Then, the following section presents the improvements in climb trajectory prediction accuracy that were achieved by the algorithm for actual Fort Worth Center traffic data in the Center/TRACON Automation System (CTAS) [3,18].…”

mentioning

confidence: 99%

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Adaptive Algorithm to Improve Trajectory Prediction Accuracy of Climbing Aircraft

Thipphavong

Schultz

Lee

et al. 2013

Journal of Guidance, Control, and Dynamics

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Aircraft climb trajectories are difficult to predict, and large errors in these predictions reduce the potential operational benefits of some advanced concepts in the Next Generation Air Transportation System. An algorithm that dynamically adjusts modeled aircraft weights based on observed track data to improve the accuracy of trajectory predictions for climbing flights has been developed. In real-time evaluation with actual Fort Worth Center traffic, the algorithm decreased the altitude root-mean-square error by about 20%. It also reduced the root-mean-square error of predicted time at top of climb by the same amount.

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Section: Establishing Proof-of-concept Throughmentioning

confidence: 99%

mentioning

confidence: 99%

Adaptive Algorithm to Improve Trajectory Prediction Accuracy of Climbing Aircraft

Thipphavong

Schultz

Lee

et al. 2013

Journal of Guidance, Control, and Dynamics

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“…Microscopic models consider each aircraft individually and reproduce precisely the physical layout of the airport and the sequencing of movements (Bilimoria et al, 2000;Sood and Wieland, 2003;George et al, 2011). These models are not well-suited to performing strategic planning under a wide range of scenarios.…”

Section: Literature Reviewmentioning

confidence: 99%

Endogenous control of service rates in stochastic and dynamic queuing models of airport congestion

Jacquillat

Odoni

2015

Transportation Research Part E: Logistics and Transportation Re

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Airport congestion mitigation requires reliable delay estimates. This paper presents an integrated model of airport congestion that combines a tactical model of capacity utilization into a strategic queuing model. The model quantifies the relationships between flight schedules, airport capacity and flight delays, while accounting for the way arrival and departure service rates can be controlled over the day to maximize operating efficiency. We show that the model estimates well the average and variability of the delays observed at New York's airports. Results suggest that delays can be extremely sensitive to even small changes in flight schedules or airport capacity.

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“…These agent-based models represent air traffic processes such as vehicle trajectories, collision avoidance, airport operation, etc. In this category of models, we can mention Air MIDAS [11][12], ACES [10][18], AgentFly [15] and tools such as AirTop [2] and CAST [6]. These approaches are capable of simulating how air traffic controllers manage aircraft as they fly and move in the airports with a high level of detail.…”

Section: Modeling Challenges For the Design Of Future Atm Systemsmentioning

confidence: 99%

Agent-Based Modeling and Simulation for the Design of the Future European Air Traffic Management System: The Experience of CASSIOPEIA

Molina

Carrasco

Martín

2014

Communications in Computer and Information Science

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Abstract. The SESAR (Single European Sky ATM Research) program is an ambitious research and development initiative to design the future European air traffic management (ATM) system. The study of the behavior of ATM systems using agent-based modeling and simulation tools can help the development of new methods to improve their performance. This paper presents an overview of existing agent-based approaches in air transportation (paying special attention to the challenges that exist for the design of future ATM systems) and, subsequently, describes a new agent-based approach that we proposed in the CASSIOPEIA project, which was developed according to the goals of the SESAR program. In our approach, we use agent models for different ATM stakeholders, and, in contrast to previous work, our solution models new collaborative decision processes for flow traffic management, it uses an intermediate level of abstraction (useful for simulations at larger scales), and was designed to be a practical tool (open and reusable) for the development of different ATM studies. It was successfully applied in three studies related to the design of future ATM systems in Europe.

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Build 8 of the Airspace Concept Evaluation System

Cited by 48 publications

References 10 publications

Adaptive Algorithm to Improve Trajectory Prediction Accuracy of Climbing Aircraft

Adaptive Algorithm to Improve Trajectory Prediction Accuracy of Climbing Aircraft

Endogenous control of service rates in stochastic and dynamic queuing models of airport congestion

Agent-Based Modeling and Simulation for the Design of the Future European Air Traffic Management System: The Experience of CASSIOPEIA

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