Publications

We have extended an analytical workload model for estimating en route sector capacity to include the impact of convective weather. We use historical weather avoidance data to characterize weather blockage, which affects the sector workload in three ways: (1) Increase in the conflict resolution task rate via reduction in available airspace, (2) increase in the recurring task load through the rerouting of aircraft around weather, and (3) increase in the inter-sector coordination rate via reduction in the mean sector transit time. Application of the extended model to observed and forecast data shows promise for future use in network flow models.

This document presents a preliminary analysis of potential departure delay reduction benefits in New York as the result of the use of the Integrated Departure Route Planning (IDRP) tool during convective severe weather avoidance programs (SWAP). The analysis is based on weather impact and air traffic data from operations between May and September 2010 in the New York metroplex region. Two methodologies were employed in the analysis: "flight pool" and "resource pool." In the flight pool methodology, individual flights with excessive taxi times were identified, and opportunities to find potential alternative reroutes using information that IDRP will provide were assessed. In the resource pool methodology, route impact minutes were tallied over several days, based on the judgment of a human analysis, and opportunities to recover capacity lost to route impacts via IDRP-identified reroutes were estimated. The flight pool methodology estimated that approximately 156 hours of delay could be saved through the use of IDRP over a full SWAP season. The resource pool methodology estimated that approximately 15% of capacity lost to convective weather impacts could be recovered via IDRP-based reroutes. It should be noted that the potential benefits are based on several assumptions that are described in detail in the text of the report. The estimation of delay savings due to reroute is also speculative. It is very difficult to ascertain when the assignment of a reroute actually makes use of underutilized capacity and when the reroute simply shifts the problem from one congested resource to another. Further research is needed to develop reliable metrics that can guide the assessment of reroute impacts on overall traffic management performance.

The Route Availability Planning Tool (RAPT) operational prototype was deployed to Chicago in the summer of 2010, the first RAPT deployment outside of the New York departure airspace for which it was originally developed. The goal of the deployment was to evaluate the adaptability of RAPT's airspace definition, departure management and weather impact models to different terminal areas throughout the National Airspace System (NAS). This report presents the results of a summer-long evaluation of the Chicago RAPT operational prototype, in which the performance of RAPT algorithms and the effectiveness of the RAPT Concept of Operations were assessed. The evaluation included observations made by researchers simultaneously stationed at O'Hare terminal (ORD), the Chicago TRACON (C90), and the Chicago Air Route Traffic Control Center (ZAU) during several days of convective weather impact and post-event analysis of air traffic data from the Enhanced Traffic Management System (ETMS) and RAPT weather impact predictions and departure management guidance. The study found that significant departure delay reduction could be achieved through the use of RAPT in Chicago, and that RAPT effectiveness in "typical" corner post airspaces like Chicago could be further increased with some modifications to the Concept of Operations, user training, and site adaptation.

When operationally significant weather affects a region of the National Airspace System (NAS) a Severe Weather Avoidance Program (SWAP) is initiated for that region. Each SWAP event is a unique mix of demand, weather conditions, traffic flow management (TFM) initiatives and traffic movement. On the day following a SWAP, the SWAP events are reviewed by FAA and airline representatives as part of the daily planning teleconference, and the TFM initiatives used are evaluated to understand their impact on the traffic flows, benefits, and disadvantages. Due to the complexity of the situation various exploratory visualizations were designed in order to evaluate aspects of the aviation environment and the responsive actions of the NAS during outbreaks of convective weather as well as to gain insights on the interaction of weather and traffic operations. From these visualizations, analyses and metrics were developed that could be used to objectively evaluate the effectiveness of TMIs. This paper will present three visualizations that have directly resulted in the development of analyses for TMIs or lead to insights into air traffic operations.

MIT Lincoln Laboratory has developed the Route Availability Planning Tool (RAPT), which provides automated convective weather guidance to air traffic managers of the NYC metro region. Prior studies of RAPT have shown high-accuracy guidance from forecast weather, but further refinements to prevent forecast misclassification is still desirable. An attribute set of highly correlated predictors for forecast misclassification is identified. Using this attribute set, a variety of prediction models for forecast misclassification are generated and evaluated. Rule-based models, decision trees, multi-layer perceptrons, and Bayesian prediction model techniques are used. Filtering, resampling, and attribute selection methods are applied to refine model generation. Our results show promising accuracy rates for multi-layer perceptrons trained on full attribute sets.

When operationally significant weather affects the National Airspace System (NAS) a Severe Weather Avoidance Program (SWAP) is initiated. Each SWAP event is a unique mix of demand, weather conditions, traffic flow management (TFM) initiatives and traffic movement. Following a SWAP, the day's events are reviewed and the TFM initiatives used are evaluated to understand their impact on the traffic flows, benefits, and disadvantages. These analyses require an accurate representation of the conditions during SWAP and objective, data-driven metrics to determine the effectiveness of the implemented TFM initiatives, and to identify opportunities for improved decision making in future events. As part of the ongoing development and evaluation of the Route Availability Planning Tool (RAPT), a departure management decision support prototype currently deployed in New York, several detailed metrics were developed to streamline these analyses. This paper focuses on metrics that address the most significant concern regarding departure flows from New York airports: the timely reopening of departure routes that have been closed due to convective weather impacts. These metrics are derived from two datasets: flight tracks from the Enhanced Traffic Management System (ETMS) to monitor the flight traffic, and route blockage from the Route Availability Planning Tool (RAPT) to determine the impact of weather on routes. RAPT automatically identifies Post-Impact-GREENs (PIGs) - the period of time when routes are clear ('GREEN') after being blocked by convective weather. Identifying PIGs early is a key element of the RAPT concept of operations, which enables traffic managers to restart traffic flow sooner along these routes, alleviating backed up ground conditions and reducing delay times for waiting flights. An automated system, that correlates PIGs identified by RAPT with departure traffic flows, calculates both the time from the appearance of each PIG until the first departure along the PIG route, and the departure rate on the route during the PIG period. Short times to first departure and high departure rates during PIGs indicate efficient departure management during SWAP. Arrival aircraft deviating into departure airspace is also managed by closing the departure route until the danger from incurring flights has passed. Arrival incursions are sometimes recorded in the National Traffic Management Log (NTML), but the extent to which the deviations occur is unmeasured. Lack of details regarding deviations limits evaluation of implemented responses and alternative actions. New algorithms comparing clear weather vs. SWAP traffic flows enables the locations and durations of incursions to be identified. Exact figures detailing incursions allows for thorough review as well as recognition of areas of frequent incursions and the potential for developing a targeted response for like situations. Full flight tracks of arriving and departing flights provide significant insight into the status of the NAS. During SWAP when the airspace capacity is decreased and airport operation rates are limited, airborne aircraft by protocol receive priority. Arrival numbers can completely dominate operations at these times both in the air and on the ground, draining the resources available for departures in particular flows or for an entire region. To convey cases where departure infrequency results from these conditions, arrival and departure counts grouped according to direction of travel are calculated on an hourly basis. Results from the automated analysis are made available on the RAPT Evaluation and Post Event Analysis Tool (REPEAT) website by 7AM ET for the FAA Northeast tactical review teleconferences, and are being tracked over the convective season for further analysis of operational performance. This paper will present the techniques used in the automated system and initial results from the analysis of operational data.

Severe weather avoidance programs (SWAP) due to convective weather are common in many of the busiest terminal areas in the US National Airspace System (NAS). In order to make efficient use of available airspace in rapidly evolving convective weather, it is necessary to predict the impacts of the weather on key resources (e.g., departure and arrival routes and fixes), with frequent updates as the weather changes. Currently, this prediction is a mental process that imposes a significant cognitive burden on air traffic managers. As a result, air traffic management in SWAP is often inconsistent and decisions result in less than optimal performance. The Route Availability Planning Tool (RAPT) is a prototype automated decision support tool, intended to help air traffic managers in convective weather SWAP, by predicting the impacts of convective weather on departure routes. Originally deployed in New York in August, 2002, RAPT has recently undergone two field evaluations (2007 and 2008) in order to test and refine its concept of operations, evaluate the accuracy and usefulness of its decision guidance, and estimate observed and potential delay reduction benefits that may be achieved as a result of its use. This paper presents the results of the 2008 performance evaluation, focusing on the concept of operations and the quality of decision support guidance. A second paper [1] presents analyses of delay reduction benefits and the operational decision making environment in which RAPT is deployed.