Representative Weather-Impact Scenarios for Strategic Traffic Flow Planning

Tien, Shin-Lai; Taylor, Christine; Wan, Yan

doi:10.2514/6.2014-2714

Cited by 3 publications

(3 citation statements)

References 11 publications

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“…Previous studies have treated each ensemble member as one trajectory of weather development through the NAS, assuming equal likelihoods of occurrence. 4,8 The SREF forecast variables from the grids where the OEP airports reside, including ceiling, visibility, wind, precipitation, and reflectivity, are used to predict airport AAR. The solid blue line shows the recorded wind speed during that timeframe, confirming the trend suggested by the aggregate behavior of the ensemble members.…”

Section: Ivapplication To Ensemble Forecast -An Illustrative Examplementioning

confidence: 99%

“…[1][2][3][4][5][6][7] To account for forecast uncertainty, [4] and [8] leveraged an ensemble forecast product to capture the wide range of capacity outcomes persistent in the planning horizon. Using a prototype simulation and evaluation capability, these works further highlighted the resulting capacity variation in developing traffic management strategies that arise as a result of the inherent differences among ensemble members.…”

Section: Introductionmentioning

confidence: 99%

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Using Ensemble Weather Forecasts for Predicting Airport Runway Configuration and Capacity

Tien

Taylor

Wan

2016

16th AIAA Aviation Technology, Integration, and Operations Conference

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Strategic air traffic flow management requires predictions of airport departure and arrival capacities several hours into the future. It is difficult to do this well because of weather forecast uncertainty. However, if the measurement of prediction uncertainty is provided, strategies can be developed to account for it. In this paper, we examine the potential for using ensemble weather products to quantify uncertainty in airport capacity prediction. An improved prediction model from previous studies that utilizes weather forecast variables to predict runway configuration and capacity is validated and then applied to each ensemble member, so that the distribution of possible capacity outcomes and prediction confidence can be obtained. Our results suggest that the performance of the prediction model has been improved, and that the forecast variation among ensemble members effectively captures the possible variations in future arrival capacity for certain airports.

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Section: Ivapplication To Ensemble Forecast -An Illustrative Examplementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Using Ensemble Weather Forecasts for Predicting Airport Runway Configuration and Capacity

Tien

Taylor

Wan

2016

16th AIAA Aviation Technology, Integration, and Operations Conference

Self Cite

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show abstract

“…Clustering can now be done using the remaining principal components. Specifically, a modified spectral clustering algorithm [18] iteratively partitions a group of solutions into two until the stopping criteria are reached. This algorithm does not require that the number of desired groups be determined a priori.…”

Section: B Clustering the Pareto Setmentioning

confidence: 99%

Generating Diverse Reroutes for Tactical Constraint Avoidance

Taylor

Liu

Wan

et al. 2018

Journal of Air Transportation

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Decision support capabilities that provide flightspecific reroutes around constraints can enable more flexible and agile management of the airspace. For this benefit to be realized, automation must reliably provide operationally-acceptable alternatives to traffic managers. This paper proposes an approach for generating a small number of diverse, feasible solutions for further evaluation by traffic managers. Using a variation on Dijkstra's shortest path algorithm, reroutes are designed for one or more flights, where multi-flight problems promote the active design of reroute flows. A multi-objective genetic algorithm is employed to evaluate trade-offs between multiple criteria of operational acceptability, removing the need to pre-define relative metric weightings. Finally, a combination of Principal Components Analysis and Spectral Clustering is used to identify distinct groups of solutions and representative reroutes that capture different trade-offs between metrics of operational acceptability. Results are generated for a historical convective weather event and evaluated for their characterization of the trade-space.

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