National Airspace System Probabilistic Traffic Flow Management in Inclement Weather

Transcription

1 National Airspace System Probabilistic Traffic Flow Management in Inclement Weather March 15, 26 George Hunter, Kris Ramamoorthy, Ben Boisvert, Ari Stassert, Anna Drabowski, Jim Phillips, Alex Huang, Fred Wieland, Greg Carr Sensis Technology Center 1

2 Probabilistic TFM Departure time Probabilistic TFM 2

3 Trajectory-based Weather Impact Analyze specific trajectory, not just flow through sector Analyze Wx impact on the specific trajectory Reroute Flight plan ZKC2 High sector Count a route as unavailable only if reasonable reroutes are also unavailable 3

4 Sector Capacity PDF Sector capacity Maximum Aggressive rerouting Example MSC results for May 1, 24. Sector ZKC2. Randomly select 3 flights that transit the sector and compute upper and lower bounds. Repeat this 1 times to check for convergence. Result: Good convergence found. 3 flights selected at random reproduce upper and lower bound estimates with low variance. No rerouting Time (15 minute steps) 4

5 Uncertain Storm Forecast Result: A forecasted sector capacity probability distribution function (PDF) For all sectors, all time horizons, all time slots Frequency Capacity max 5

6 Computing Airspace Demand and Capacity Probability Sector Capacity Probability Sector Capacity Probability Frequency Capacity Short look-ahead time Clear weather Extreme weather clear Accurate storm forecast Frequency Capacity clear Long look-ahead time Medium convective weather Inaccurate storm forecast Probability Probability Probability Now Predicted Sector Capacity Predicted Sector Capacity Predicted Sector Capacity Probability Probability Probability Predicted Sector Capacity Predicted Sector Capacity Predicted Sector Capacity Probability Probability Probability Predicted Sector Capacity Predicted Sector Capacity Hours from now Predicted Sector Capacity Many factors impact PDF shape Capacity uncertainty grows dramatically with length of look-ahead 6

7 Example Sector Loading PDF Probability minute look ahead time 12 aircraft predicted 6 have departed Predicted Sector Loading 7

8 Congestion Cost Time History Predicted loading overlaps predicted capacity causing non-zero congestion cost Mean predicted capacities Mean predicted load (at gate and en route) 8

9 Congestion: Load vs Capacity Predicted load Predicted capacity Predicted Weather Congestion probability Congestion map: a combination of the predicted weather impact and predicted traffic 27 July 24 9

10 145 MidAtlantic, 27Jul4 1

11 22 Congestion Map 11

12 ETMS Reroute Count Scaled to 47k flights ~1% flights rerouted > 3% path stretch 12

13 Significantly Fewer Rerouter With Our Flight Planner 264 reroutes 13

14 ETMS Congestion Profile #Overloaded sectors =

15 Congestion/Delay Tradeoff Comparison Today s system (~1,77 congestion events and ~25 minutes delay) 1 #Congestion events Predeparture delay only WRT MAP Predeparture delay & rerouting Delay (minutes) Predeparture delay only 15

16 ETMS Congestion Distribution Mean overload = 138% 16

17 Mean Overload Comparison 6 Mean congestion (ops) ETMS mean overload count = Delay (minutes) 17

18 An Improved NAS Reduced congestion and delay using trajectory-based Probabilistic TFM Probabilistic TFM solutions Today s technology level 18

19 Traffic Planning with Uncertainty Weather impacts airspace, but the forecasted capacity and loading are uncertain. The result: 35 3 Robust traffic flow in the future NAS Perfect Persistence Actual Observed traffic Mean >3 dbz Dwell Time (min) Frequency Capacity max Trajectory-based traffic flow optimization using dynamic congestion map. Predicted load Congestion probability Predicted capacity Traffic load exceeding capacity => congestion. 19

20 Backup 2

21 Probabilistic TFM Result: A forecasted sector capacity probability density function (PDF) For all sectors, all time horizons, all time slots Frequency Capacity max 21

22 Mean Overload Comparison 6 Mean congestion (ops) ETMS mean overload count = Delay (minutes) 22

23 Traffic Planning with Uncertainty Weather impacts sector airspace, but the forecasted capacity and loading are uncertain. 4 The result: 35 A 3 robust traffic 25 2 flow in the 15 future NAS Perfect Persistence Actual Observed traffic Mean >3 dbz Dwell Time (min) Frequency Capacity max Trajectory-based traffic flow optimization using dynamic congestion map. Predicted load Congestion probability Predicted capacity Traffic load exceeding capacity => congestion. 23