Predeparture Uncertainty and Prediction Performance in Collaborative Routing Coordination Tools

The collaborative routing coordination tools concept demonstration and evaluation prototype is a tool to help the Federal Aviation Administration detect traffic flow problems in advance, generate reroute-based problem resolutions, and evaluate the resolution strategies. The tool does this by modeling four-dimensional aircraft trajectories and using them to predict demand for sector usage. The predictions are affected by various sources of uncertainty in the national airspace system. Therefore, it is useful to understand the contribution of this uncertainty to the tool's predictive error. A methodology was developed and used to assess the impact of predeparture uncertainty on the prototype tool's prediction performance. The tool's trajectory modeling and sector load prediction are described, the methodology used to assess the tool's prediction performance is presented, and the results of the predeparture uncertainty analysis are discussed. The analysis is based on tool predictions made for two air route traffic control centers. Tool runs were made against recordings of actual air traffic data on two good weather and two bad weather days. Analysis of run data showed that predeparture uncertainty is a greater contributor to sector prediction error than en route uncertainty. Because predeparture uncertainty is reflected in departure time estimate, research is recommended to identify methods to improve the accuracy of this estimate.