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October 31, 20011 Metron Aviation, Inc. Dan Rosman Assessing System Impacts: Miles-in-Trail and Ground Delays.

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Presentation on theme: "October 31, 20011 Metron Aviation, Inc. Dan Rosman Assessing System Impacts: Miles-in-Trail and Ground Delays."— Presentation transcript:

1 October 31, 20011 Metron Aviation, Inc. Dan Rosman Assessing System Impacts: Miles-in-Trail and Ground Delays

2 October 31, 20012 En-Route TFM Issues What Problems are we Trying to Solve? –Sector Congestion –System Predictability and Results of Prediction Errors –Flight Route Coordination –Equitable Allocation of Resources –Efficient Use of Resources

3 October 31, 20013 Ground Delays and MIT Restrictions Ground delay programs and ground stops prevent airborne delays but may result in underutilization of arrival capacity because of changing demand Miles-in-Trail provides an airborne reservoir which may result in greater airborne holding costs and increase air traffic control workload Need some combination of strategic initiatives that is market driven and optimizes trade off between airborne holding and ground delay costs

4 October 31, 20014 Ground Delays and MIT Restrictions There are currently 203 daily historically validated miles- in-trail restrictions On average, 186 dynamic miles-in-trail restrictions occur each day –13.5 flights impacted by each restriction –8.5 flights affected for each hour that MIT restriction was in place In 2000, there were 1083 ground delay programs averaging 6.5 hours in length per program

5 October 31, 20015 Approach NAS-Wide System Impact Assessment Tools are Needed –What impact does an en-route constraint have on the airport operation (arrival, departure, surface)? –What about surface constraints on the en-route operation? –These impacts are significant and affect system performance –TFM constraints impact equity Collaborative En-Route Flow Management Tool (C-Flow) –Prototype System Impact Assessment Tool is Currently Being Developed –Validated through quantitative analysis –Validated through human-in-the-loop simulation

6 October 31, 20016 C-Flow Concept C-Flow Provides Common Visualization of Flow Restrictions and Impacts Resultant airport flows Sector counts Airborne delay in sectors C-Flow Dynamically Updates Impact Predictions ATC Specialists Can Evaluate the Need for Restrictions Can a restrictions be dropped? Are new restrictions needed? New Restrictions can be Planned by Evaluating the Predicted Impact on Flow Rates, Delays and Equity 30 20 ORD GDP

7 Upstream Effects of Traffic Management Restrictions 20 Delay Buildup Flow Shut-off Airport Gridlock Ground Stop ZOB48

8 Cumulative Effects of Traffic Management Restrictions Even Arrival Flow with GDP 20 Slots Lost with MITs

9 C-Flow GUI Display

10 October 31, 200110 System Impact Analysis Using C-Flow, Analyzed LAX Traffic Management Program on May 1, 2001 –Ground delay program initiated after host computer problems at ZLA –ARTCCs adjacent to ZLA also added miles-in-trail restrictions –ZLA also assigned release times for internal departures –Significant delays result But some delay was unnecessary Excess unused capacity at LAX

11 October 31, 200111 System Impact Analysis C-Flow Modeled Four Major TFM Elements: –Ground delay program –Miles-in-trail restrictions –Internal departure release times –Sequencing and separation of flights The Results Showed Good Correlation with Actual Operations –An operational C-Flow could help avoid the under- delivery problem

12 October 31, 200112 Simulation of LAX Event 5/1/2001 Program 1630Z to 2359Z, LAX at 60/64 Arrivals per Hour Bars show arrival sector loading and anticipated delay to be absorbed under simulated flow. Note the significant delay indicated (ZAB92). MIT parameters based on actual restrictions applied

13 October 31, 200113 Simulation of LAX Event 5/1/2001

14 October 31, 200114 Current C-Flow Development Near Real-Time Infrastructure Under Development –POET database Allow trajectory predictions to be stored in database Compute sector entry and exit times for predictions Produce sector load metrics from predictions Trajectory Prediction (non-developmental item) –Integrate latest trajectory prediction software –Collect and archive RUC2 wind data Graphical User Interface (developed as variant of GCDR)

15 October 31, 200115 Future Development Phases Phase 1 –Predict and display traffic flows that result from miles-in-trail restrictions obtained from the National Log Program In downstream sectors and to airports Assist ATC specialists to determine if MIT restrictions are necessary Phase 2 –Over/Under constrained decision support due to MIT and possibly GDP restrictions Provide automated alert if MIT restrictions –are not enough to avoid excess demand downstream –are more than necessary to avoid excess demand downstream

16 October 31, 200116 Development Phases (cont.) Final Product: System Impact Assessment Tool –Assist ATC specialists in selecting between strategies: Re-routes Ground stops GDPs Sector GDPs Miles-in-trail Other initiatives –Predict and display flow and equity of each strategy or a combination of strategies

17 October 31, 200117 Evaluation Phases Shadow Operations and Evaluation –Analytical evaluations to assess sector demand prediction accuracy –Demonstrations to users to obtain subject matter expert feedback War-Game –Human-in-the-loop simulation of ATCSCC, TMU and AOC –Simulated evaluation of use of C-Flow for What-If evaluations of traffic management strategies Communication of predicted congestion and delays to airlines Goal of War-Game –Validation of tool capabilities –Identification of missing capabilities –Validation/Improvement of user interface –Development of procedures for use of tool –Identification of methods for collaborative decision making

18 October 31, 200118 Summary Air traffic community has a clear need for system impact assessment tools and analysis C-Flow is currently being developed to meet that need -Ground stop and ground delay models -MIT model Current prototype needs to be expanded to incorporate other traffic management initiatives End product will allow user to evaluate tradeoffs between initiatives and arrive at efficient and fair allocation of resources that solve en-route congestion problems

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