1. Turning Goals Into Reality: Revolutionizing Air Transportation Mobility George L. Donohue George Mason University

2. GEORGE MASON UNIVERSITY2 Source: BTS 1998

3. GEORGE MASON UNIVERSITY3 Premise #1 Air Transportation Hub and Spoke Systems –Network of Airport and Sector Queue’s –Approaching Max Capacity Today –Models Predict Higher Delays in 2010, even with all planned new runways and new technology

4. GEORGE MASON UNIVERSITY4 Hub and Spoke Network Completely Connected Network = 2(N-1) Flights (eg., 50 Airports, 98 Flights) Ref: J. Hansman, MIT

5. GEORGE MASON UNIVERSITY5 Hyperbolic Growth in US Delay (>15min/1000 operations) vs. Airport Capacity Fraction

6. GEORGE MASON UNIVERSITY6 Premise #2 Avoiding Network Hubs Exacerbates Airspace Management Limitations –Small Aircraft Traffic Grows like N 2 vs. 2N –Controller Cognitive Workload Limitations –Radio Frequency Spectrum Limitations

7. GEORGE MASON UNIVERSITY7 Fully Connected Network Completely Connected Network = N(N-1) (eg., 50 Airports, 2450 Flights) Ref: J. Hansman, MIT

8. GEORGE MASON UNIVERSITY8 Comparison of US and European Delay (min./flt.) vs. Airport Capacity Fraction

9. GEORGE MASON UNIVERSITY9 Backup

10. GEORGE MASON UNIVERSITY10 Macro Capacity Model C max = 2 x C AR MAX S  i (XGR) i – C AS MAX  K A K. A K = (A/C REQUEST – A/C ACCEPT ) / C AS MAX C AR MAX = 64 Arrivals/Hour C AS MAX = 120 Aircraft/Sector/Hour

11. GEORGE MASON UNIVERSITY11 Aircraft Arrival Rate vs. Separation Distance

12. GEORGE MASON UNIVERSITY12 Arrival Spacing is Critical to Capacity and Safety

13. GEORGE MASON UNIVERSITY13 16 US Airports in Northeast Triangle Representing 7.6 X 10 6 Operations/Yr

14. GEORGE MASON UNIVERSITY14 US Airport Runway Utilization 16 Airports in NE Triangle

15. GEORGE MASON UNIVERSITY15 16 European Airports Representing 4.3 X 10 6 Operations/Yr.

16. GEORGE MASON UNIVERSITY16 European Airports in Comparison

17. GEORGE MASON UNIVERSITY17 European Airport Utilization 16 Airports

18. GEORGE MASON UNIVERSITY18 Hyperbolic Growth in US Delay (min./flt.) vs. Airport Capacity Fraction

19. GEORGE MASON UNIVERSITY19 Conclusions Air Transportation Systems can be Represented as a Network of FCFS Queue’s with a Loosely Coupled Central Flow Control The US is operating at a relatively High Airport Capacity Fraction with increasing Delay Europe is operating at a relatively Low Airport Capacity Fraction with sector workload producing high delays imposed through Central Flow Control Delays of 2 min per aircraft seem to be the minimum airspace induced delay independent of Airport Capacity