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© 2010 The MITRE Corporation. All Rights Reserved. Sector Capacity Prediction for Traffic Flow Management Lixia Song April 13 th, 2010
© 2010 The MITRE Corporation. All Rights Reserved. 2 En Route Congestion Uncertain weather forecasts indicate current and future loss of airspace capacity… Uncertain traffic forecasts provide airspace demand… If demand exceeds capacity, delays will occur and safety may be compromised. Role of TFM: Balance demand vs. capacity. Key function: Predicting capacity/congestion. Required: A good metric of capacity/congestion. Air traffic control sectorCongestion Alerts
© 2010 The MITRE Corporation. All Rights Reserved. 3 What is Sector Capacity? Aircraft Count (N) Workload Overload Threshold Sector Capacity Increasing Complexity Cited from EUROCONTROL Experimental Center Note No. 21/03 EDYCOLO Wednesday 4 July 2001
© 2010 The MITRE Corporation. All Rights Reserved. 4 A Good Sector Capacity Metric for En Route TFM Decision Support… Better represents sector workload, and workload threshold, considering traffic complexity Is intuitive and relevant to human decision-makers Provides insight into congestion resolution options Is predictable at useful look-ahead times (30 min – 2 hr) Captures impact of convective weather
© 2010 The MITRE Corporation. All Rights Reserved. 5 Flow Structure to Represent Traffic Complexity for TFM Traffic Complexity Detailed factors (traffic characteristics) for Dynamic Density Controller Workload Air Traffic Control Aggregated factors (flow characteristics) for predicting sector capacity Traffic Flow Management –Aggregate flow variables are more easily predicted at TFM time frames than aircraft interaction variables –Flow structure is tightly related to controllers control strategy –Flow structure provides insight into congestion resolution options
© 2010 The MITRE Corporation. All Rights Reserved. 6 The Flow Pattern Based Approach Identify the primary set of traffic flow patterns for each sector Best Match Predicted flow pattern Assess the sector capacity for each pattern of the set Predict the sector capacity through pattern recognition
© 2010 The MITRE Corporation. All Rights Reserved. 7 Under Severe Weather Impact Case A Case B Case C
© 2010 The MITRE Corporation. All Rights Reserved. 8 Under Weather Impact --- Available Sector Capacity Ratio Traffic flow pattern is predicted with flows defined by sector transit triplets LLs CWAM1 model is used to estimate the WAAF AvailableFlowCapacityRatio is determined by mincut theory (inspired by METRON)
© 2010 The MITRE Corporation. All Rights Reserved. The Effect of Convective Weather on Sector Capacity Compared three sector weather impact indexes –2-D weather coverage –3-D WAAF coverage –Flow-based AvailableSectorCapacityRatio Answer the following questions with statistical analysis of historical data –Which sector weather impact index has the strongest correlation with actual sector capacity –Whats the predictability of these sector weather impact indexes 9
© 2010 The MITRE Corporation. All Rights Reserved. Results from Initial Correlation Analysis 10 June and July 2007 traffic and weather data were collected The 95 th percentile of sector throughput is used as the estimated actual sector capacity Initial analysis on 48 high sectors shows –Flow-based AvailableSectorCapacityRatio has the strongest linear correlation with sector capacity for sectors with dominant flows The AvailableFlowCapacityRatio of the dominant flow has strong linear correlation with the flow and sector capacity –Probabilistic CWAM1 with right threshold is needed to calculate WAAF Initial analysis on 43 low sectors shows –Both Deterministic and probabilistic CWAM1 do not work well for most of the low sectors
© 2010 The MITRE Corporation. All Rights Reserved. 11 Linear Correlation between 95 th Percentile of Sector Throughput and Sector Weather Impact Indexes
© 2010 The MITRE Corporation. All Rights Reserved. 12 Linear Correlation between 95 th Percentile of Flow Throughput and AvailableFlowCapacityRatio ZDC16-ZDC12-ZDC18 ZDC72-ZDC12-ZDC18 ZDC16-ZDC12-ZDC17 ZDC16 ZDC72 ZDC12 ZDC18 ZDC17
© 2010 The MITRE Corporation. All Rights Reserved. 13 Correlation between 95 th Percentile of Sector Throughput and AvailableFlowCapacityRatio
© 2010 The MITRE Corporation. All Rights Reserved. Initial Results of Predictability Analysis Predictability of 2D weather coverage and 3D WAAF coverage are comparable The predictability of available flow capacity ratio is relatively lower than the other two 3D WAAF coverage and the reduced flow capacity ratio tend to be over-predicted –Both due to the over-prediction of CIWS echo top 14
© 2010 The MITRE Corporation. All Rights Reserved. Predictability Comparison 15
© 2010 The MITRE Corporation. All Rights Reserved Sensitivity to Weather Location Omincut Cases with the prediction to be 0 but the actual to be 1
© 2010 The MITRE Corporation. All Rights Reserved. Future Research Develop probabilistic model to capture weather prediction uncertainty, especially weather shape and location Improve the flow-based model with more research on translating the flow blockage to sector capacity reduction –Consider the impact of weather on traffic complexity Enhancing available flow capacity ratio calculation to more accurately estimate impact of transition flows Flow capacity prediction and usage in both current and future operational environment –This analysis reveals the directional (flow) capacity usage in the current operational environment NAS-Wide analysis is necessary 17
© 2010 The MITRE Corporation. All Rights Reserved. Questions for FCA Capacity What is FCA capacity? What is a good metric of FCA capacity? How to predict the nominal FCA capacity? How to reduce the FCA capacity under weather impact? 18
© 2010 The MITRE Corporation. All Rights Reserved. Back Up
© 2010 The MITRE Corporation. All Rights Reserved Sector Transit Triplets to Represent Flows 1/6/04 14Z ZDC12 Major Triplets (actual traffic) Flows are the triplets that have at least two aircraft within the given time period.
© 2010 The MITRE Corporation. All Rights Reserved. 21 Identify Primary Set of Traffic Flow Patterns with Self-Organizing Maps (SOMs) P 1 : Major Flow P 2 : Major Flow P 3 : Major Flow Others P 1 : Major Flow P 2 : Major Flow P 3 : Major Flow Others Unified distance matrix visualizes distances between neighboring traffic flow patterns, and helps to see the cluster structure of the traffic flow patterns Each component plane shows the values of each feature in the patterns organized in U-Matrix
© 2010 The MITRE Corporation. All Rights Reserved. 22 Assessing Sector Capacity Through Observing System Performance
© 2010 The MITRE Corporation. All Rights Reserved. 23 Weather Avoidance Altitude Field (WAAF) LLs CWAM1
© 2010 The MITRE Corporation. All Rights Reserved. 24 Example Available Ratio of Flow Capacity
© 2010 The MITRE Corporation. All Rights Reserved. 25 Flights Went Through Mincut to Avoid Weather
© 2010 The MITRE Corporation. All Rights Reserved. Predictability Comparison 26
© 2010 The MITRE Corporation. All Rights Reserved. Predictability Comparison 27
© 2010 The MITRE Corporation. All Rights Reserved. Predictability Comparison 28
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