Weather Integration for Strategic Traffic Flow Management

Transcription

1 The MITRE Corporation s Center for Advanced Aviation System Development Approved for Public Release; Distribution Unlimited Weather Integration for Strategic Traffic Flow Management Dr. Christine Taylor Principal Simulation and Modeling Engineer 27 October, 2015

2 Strategic TFM Planning for Weather 2 Probabilistic forecasts identify regions of potential weather activity 12Z 14Z 16Z Source: Short Range Ensemble Forecast (SREF) for 28 July, 2014 What is the range and likelihood of different weather scenarios occurring? What are the potential scenarios of ATM impacts? What options are available to mitigate congestion and when do we have to act?

3 Flow Contingency Management (FCM): Generate a Congestion Scenarios 3 FCM provides a scientific approach for strategic TFM decision-making Sector congestion Congestion Scenarios Scenario #1 Prob. = Low Arrival Delays Legend Low Med High Departure Delays Scenario #2 Prob. = Med Scenario #3 Prob. = Med Provides delays by Origin Destination and Time [Source: MITRE/CAASD] 1200Z 1400Z Planning Horizon 1600Z Develops a common understanding of the problem among stakeholders

4 Flow Contingency Management (FCM): Evaluate TMI Plans 4 FCM provides a scientific approach for strategic TFM decision-making [Source: MITRE/CAASD] Before 1200Z Scenario #1: Prob. = Low Metric Ground Delay Sector Delay Schedule Integrity Airspace Flow Program (AFP) Ground Delay Program (GDP) After Metric Ground Delay Sector Delay Schedule Integrity Provides quantitative analysis of potential plans prior to implementation

5 Flow Contingency Management (FCM): Design Strategies under Uncertainty 5 FCM provides a scientific approach for strategic TFM decision-making Side-by-side Evaluation Airspace Flow Program (AFP) Airspace Flow Program (AFP) Ground Delay Program (GDP) Scenario #1: Prob. = Low [Source: MITRE/CAASD] Metric Ground Delay Sector Delay Schedule Integrity Ground Delay Program (GDP) Metric Ground Delay Sector Delay Schedule Integrity Scenario #2: Prob. = Med Enables fact-based discussions for strategic planning development

6 Generate Congestion Scenarios Forecast Congestion 6 Ensemble weather forecast Capacity Prediction Predict Airspace Capacity Predict Airport Capacity Capacity Scenarios Provides time history of weatherimpacted sector capacities & airport AARs and ADRs Congestion Forecast Demand Prediction Flight plans Historical traffic Current TMIs Demand Forecast Origin-Destination (O-D) pair operations count per 15 min. Routes defined as sector lists Simulate Traffic Flow-based model enables real-time computation Sector and Airspace congestion shown as increasing darker colors [Source: MITRE/CAASD]

7 Generate Congestion Scenarios Generate Capacity Scenarios 7 Capacity Prediction Ensemble weather forecast Predict Airspace Capacity Predict Airport Capacity Capacity Scenarios Source: Song, et al (2009) Joint MITRE/WSU Research Source: Dhal, et al., (2014)

8 Generate Congestion Scenarios Identify Congestion Scenarios 8 Congestion Forecast Cluster Scenarios Clustering Process Identify critical forecast features Evaluate scenarios for similarities Cluster scenarios on diverging features over forecast time 12z-14z [Source: MITRE/CAASD]

9 Generate Congestion Scenarios Identify Congestion Scenarios 9 Congestion Forecast Cluster Scenarios Clustering Process Identify critical forecast features Evaluate scenarios for similarities Cluster scenarios on diverging features over forecast time S1: p =2/21 S2: p =2/21 S3: p= 17/21 12z-14z [Source: MITRE/CAASD]

10 Generate Congestion Scenarios Identify Congestion Scenarios 10 12Z 14Z 16Z Congestion Scenarios S1: p =2/21 S2: p =2/21 S3: p= 17/21 [Source: MITRE/CAASD]

11 Evaluate TMI Plans Identify Historical TMIs 11 Ensemble weather forecast Capacity Scenarios [manual what-if ] Performance Flight plans Historical traffic Demand Forecast Simulate Traffic Proposed TMI Plan Match 1: 21:00Z Current TMIs Congestion Scenarios Match 2: 23:00Z Database of historical forecasted and actual events Event Classification Historical Events Classify Features Identify Historical TMIs Feature-TMI Groupings Pre-defined groupings of similar events, updated regularly [Source: MITRE/CAASD]

12 Evaluate TMI Plans Classify Historical Events 12 Historical Event Database Forecasted weather Forecasted demand Planned TMIs Performance goals Actual weather Track data TMI Revisions Performance measure Historical Features Location of impact Timing of congestion Severity of Congestion Classify Features Cluster Features - TMIs Feature-TMI Groupings Any attribute that signals TMIs

13 Design Strategies under Uncertainty Generate TMI Options 13 [automation-assisted design] Ensemble weather forecast Capacity Scenarios Goals Flight plans Historical traffic Demand Forecast Simulate Traffic [many times] Generate TMI Options TMI Plan Options & Performance Current TMIs Congestion Scenarios Historical Options Set Historical Events Feature-TMI Groupings Identify Historical TMIs TMI Start Time Duration Rate GDP 15:00 23: hours /hr. AFP 15:00 23: hours /hr. Reroutes 17:00 20: hours

14 Design Strategies under Uncertainty Design TMI Plan Options 14 Congestion Scenarios Historical Options Set TMI Start Time Duration Rate GDP 15:00 23: hours /hr. AFP 15:00 23: hours /hr. Reroutes 17:00 20: hours Generate TMI Options Select TMI Parameters Performance Objectives, Risk Measures Proposed Restriction TMI Plan Option Scenario 1 Possible Restrictions Scenario 2 Possible Restrictions Scenario 3 Possible Restrictions Simulate Traffic Evaluate Objectives TMI Plan Option TMI Plan 1 Option TMI Plan 2 Option 3 TMI Plan Options Performance Proposed Possible Restrictions Proposed Restrictions Possible Restrictions Proposed Restrictions Possible Restrictions Restrictions

15 15 Comparing Strategy Performance WI Scenarios Probability Fixed Adaptive S1 2/ S2 2/ S3 17/ Strategy Objective Z Decision Fixed EWR 25 Adaptive BOS 40 [Source: Taylor, et al., 2015]

16 16 Discussion FCM takes the strategic planning process from reactive to proactive Analyze problems before they start Develop mitigation strategies based on analytical evaluation Opportunity to evolve the decision making paradigm Automation can help identify problems and develop solutions Quantify capacity impacts Gain insight from historical information Generate and evaluate solutions Success means a more efficient, more repeatable, and more transparent TFM system

17 Thanks!

18 18 NOTICE This work was produced for the U.S. Government under Contract DTFAWA-10- C and is subject to Federal Aviation Administration Acquisition Management System Clause , Rights In Data-General, Alt. III and Alt. IV (Oct. 1996). The contents of this document reflect the views of the author and The MITRE Corporation and do not necessarily reflect the views of the FAA or the DOT. Neither the Federal Aviation Administration nor the Department of Transportation makes any warranty or guarantee, expressed or implied, concerning the content or accuracy of these views The MITRE Corporation. All Rights Reserved.