Traffic Stability and Capacity in Decentralized Airspace

1. The Relationship Between Traffic Stability and Capacity for Decentralized Airspace7thInternational Conference for Research in Air Transportation June 22, 2016 Emmanuel Sunil, Jerom Maas, Joost Ellerbroek, Jacco Hoekstra and Martijn Tra

2. Outline Introduction Previous Research on Stability and Capacity Alternate Model Relating Stability and Capacity Hypothesized Relationship between DEP and Density Capacity Measurement for Decentralized Airspace Conclusions

3. 1. Introduction

4. Decentralized Airspace #[J.Hoekstra et al 2002] Decentralization: Transferring the traffic separation responsibility from the ground to each individual aircraft Expected to increase en-route capacity Significant research on airborne Conflict Detection and Resolution (CD&R) algorithms and interfaces Not enough research on airspace design and capacity Introduction - Previous Research - Alternate DEP Model - Hypothesis - Capacity Measurement - Conclusions

5. Overview of PhD Research • Explicit Structure • Procedural mechanism for a priori separation of aircraft by imposing constraints on aircraft degrees of motion • Implicit Structure • Self organization as a result of Conflict Resolution (CR) Decentralized Airspace Structure • Capacity Models • Methods to measure and predict capacity of decentralized airspace Introduction - Previous Research - Alternate DEP Model - Hypothesis - Capacity Measurement - Conclusions

6. Explicit Airspace Structure # Zones Tubes Full Mix Four Airspace Concepts of Increasing Structure Layers Four concepts compared using fast-time simulations #[E. Sunil et al 2016] Introduction - Previous Research - Alternate DEP Model - Hypothesis - Capacity Measurement - Conclusions

7. What is Capacity for Decentralized Airspace? • Air traffic controller workload not relevant for decentralization • Capacity is density at which airspace becomes saturated • Saturation => Variation of airspace performance metrics with density • Safety • Efficiency • Stability • … Introduction - Previous Research - Alternate DEP Model - Hypothesis - Capacity Measurement - Conclusions

8. Conflicts vs. Intrusions < dsep Conflict Intrusion • Conflicts are predicted intrusions within the look-ahead time • Intrusions occur when the minimum separation requirements are violated

9. Airspace Stability B 1 A C Introduction - Previous Research - Alternate DEP Model - Hypothesis - Capacity Measurement - Conclusions

10. Airspace Stability B 1 A C 2 Introduction - Previous Research - Alternate DEP Model - Hypothesis - Capacity Measurement - Conclusions

11. Airspace Stability B 3 1 A C 2 Introduction - Previous Research - Alternate DEP Model - Hypothesis - Capacity Measurement - Conclusions

12. Airspace Stability B 3 1 A C 2 Conflict Chain Reactions Domino Effect Parameter# #[K. Bilimoria et al 2000] [J. Krozel et al 2000] Introduction - Previous Research - Alternate DEP Model - Hypothesis - Capacity Measurement - Conclusions

13. Domino Effect Parameter (DEP) CR = Conflict Resolution #[K. Bilimoria et al 2000] [J. Krozel et al 2000]

14. Airspace Stability B 3 1 A C 2 Introduction - Previous Research - Alternate DEP Model - Hypothesis - Capacity Measurement - Conclusions

15. DEP Examples S1 S2 S1 = 1 S2 = 3 Introduction - Previous Research - Alternate DEP Model - Hypothesis - Capacity Measurement - Conclusions

16. DEP Examples S1 S2 S1 = 1 S2 = 3 S2 S1 S1 = 3 S2 = 6 Introduction - Previous Research - Alternate DEP Model - Hypothesis - Capacity Measurement - Conclusions

17. Domino Effect Parameter (DEP) • Number of secondary conflicts per primary conflict • Higher DEP Lower stability • Uses • Compare performance of different CR methods • Measure capacity of decentralized airspace Introduction - Previous Research - Alternate DEP Model - Hypothesis - Capacity Measurement - Conclusions

18. Airspace Capacity • Stability • Domino Effect Parameter • Efficiency • Safety Introduction - Previous Research - Alternate DEP Model - Hypothesis - Capacity Measurement - Conclusions

19. 2. Previous Research on Stability and Capacity

20. Previous Research Relating Stability and Capacity # Where: = separation minima = look-ahead time # If and then #[M. Jardin et al. 2004] Introduction - Previous Research - Alternate DEP Model - Hypothesis - Capacity Measurement - Conclusions

21. Conflict Rate With and Without Conflict ResolutionExperimental Evidence for a Decentralized Direct Routing Concept Density • Conflict rate with and without CR is not always same • Assumption 2 is not valid for all densities Introduction - Previous Research - Alternate DEP Model - Hypothesis - Capacity Measurement - Conclusions

22. Effect of Conflict Rate on DEP Low Density Simulations# High Density Simulations % Density #[J. Maas et al 2016] %[E. Sunil et al 2016] • Same CR algorithm (MVP) in both studies: • DEP negative for a range of low densities • DEP positive for higher densities Introduction - Previous Research - Alternate DEP Model - Hypothesis - Capacity Measurement - Conclusions

23. How can DEP be Negative? S1 S2 S2 = 3 S1 = 4 Conflict Resolution can reduce the total number of conflicts for some densities and some CR methods Introduction - Previous Research - Alternate DEP Model - Hypothesis - Capacity Measurement - Conclusions

24. Previous Research Relating Stability and Capacity Does not account for negative DEP at any density 2 Assumptions: • Conflict resolution maneuvers increase the amount of airspace searched for conflicts • The conflict rate (per unit time/distance) is the same with and without conflict resolution Introduction - Previous Research - Alternate DEP Model - Hypothesis - Capacity Measurement - Conclusions

25. 3. Alternate Model Relating Stability and Capacity

26. Overview of Derivation Main Difference: Conflict rate with and without resolution are not required to be equal Expected number of conflicts per aircraft: Without conflict resolution During one resolution maneuver With conflict resolution Note: Derivation not complete, but current form provides insights on capacity Introduction - Previous Research - Alternate DEP Model - Hypothesis - Capacity Measurement - Conclusions

27. Number of Conflicts Without Conflict ResolutionPer Flight Proportion of area searched for conflicts • Where: • = Number of conflicts per flight with no resolution • = Conflict rate with no resolution • = Separation minima • = Average speed of all aircraft • = Conflict probability no resolution = Look-ahead time = Average flight time with no resolution = Observation time = Observation area Introduction - Previous Research - Alternate DEP Model - Hypothesis - Capacity Measurement - Conclusions

28. Number of Conflicts During OneResolutionPer Flight During a resolution, the time spent searching for conflicts is equal to the look-ahead time Where: = Number of conflicts per flight during 1 resolution = Conflict rate with resolution = Separation minima = Average speed of all aircraft • = Conflict probability with resolution • = Look-ahead time • = Observation time • = Observation area Introduction - Previous Research - Alternate DEP Model - Hypothesis - Capacity Measurement - Conclusions

29. Number of Conflicts WithConflict ResolutionPer Flight With conflict resolution, each conflict causes as an extra area to be searched for conflicts, but not flown threw. Introduction - Previous Research - Alternate DEP Model - Hypothesis - Capacity Measurement - Conclusions

30. DEP Model Introduction - Previous Research - Alternate DEP Model - Hypothesis - Capacity Measurement - Conclusions

31. 4. Hypothesized Relationship between DEP and Density

32. The Three Components of the DEP • Where: • = Conflict probability with resolution • = Conflict probability without resolution • = Total number of aircraft during observation time with resolution • = Total number of aircraft during observation time without resolution • = Average flight time with resolution • = Average flight time without resolution • = Number of conflicts per flight during 1 resolution Introduction - Previous Research - Alternate DEP Model - Hypothesis- Capacity Measurement - Conclusions

33. Hypothesis: Domino vs. Density If , If, every conflict resolution will cause a new conflict, andall aircraft will perpetually be in conflict Introduction - Previous Research - Alternate DEP Model - Hypothesis- Capacity Measurement - Conclusions

34. Hypothesis: Efficiency vs. Density Flight time with conflict resolution increases nonlinearly as the number of conflicts increases with density Introduction - Previous Research - Alternate DEP Model - Hypothesis- Capacity Measurement - Conclusions

35. Modified Voltage Potential (MVP) No Resolution MVP #[J.Hoekstra2001] MVP# • Reduces relative velocities • Increases distances between aircraft Introduction - Previous Research - Alternate DEP Model - Hypothesis- Capacity Measurement - Conclusions

36. Hypothesis: Safety vs. DensityFor MVP MVP is hypothesized to reduce conflict probabilities for some densities by dispersing the over the available airspace Introduction - Previous Research - Alternate DEP Model - Hypothesis- Capacity Measurement - Conclusions

37. Hypothesis: DEP vs. Density x x Introduction - Previous Research - Alternate DEP Model - Hypothesis- Capacity Measurement - Conclusions

38. Hypothesis: DEP vs. Density x x ? Introduction - Previous Research - Alternate DEP Model - Hypothesis- Capacity Measurement - Conclusions

39. 5. Capacity Measurement for Decentralized Airspace

40. The Three Components of the DEP Introduction - Previous Research - Alternate DEP Model - Hypothesis- Capacity Measurement - Conclusions

41. Definition of Capacity for Decentralized Airspace Introduction - Previous Research - Alternate DEP Model - Hypothesis - Capacity Measurement - Conclusions

42. Definition of Capacity for Decentralized Airspace Theoretical Definition Capacity is defined as the lowest density at which the rate of change of safety/efficiency/stability metrics tend to infinity Capacity is limitedby the safety or efficiency or stability performance of the airspace Introduction - Previous Research - Alternate DEP Model - Hypothesis - Capacity Measurement - Conclusions

43. Theory vs. Reality • In practice capacity is also determined by airline economics => efficiency driven • Public will not accept asymptotic behavior of safety as a capacity limit • Practical capacity hard to quantify • Workload varies from ATCo to ATCo • But, the theoretical capacity definition is a useful and unbiased benchmark: • Capacity limits for different methods of organizing traffic • Effect for different CR methods on capacity Introduction - Previous Research - Alternate DEP Model - Hypothesis - Capacity Measurement - Conclusions

44. 6. Conclusions

45. Summary The Domino Effect Parameter (DEP) measures the number of secondary conflicts per primary conflict A model of the DEP has been derived that does not require the conflict rate to be the same with and without conflict resolution: DEP relates safety, stability and efficiency to capacity for decentralized airspace Capacity is defined as the lowest density at which the rate of change of safety/efficiency/stability metrics tend to infinity Introduction - Previous Research - Alternate DEP Model - Hypothesis - Capacity Measurement - Conclusions

46. Next Steps in PhD Research… • Validate the hypothesized relationships between DEP components and density • Using fast-time simulations • Wide range of densities • Complete the derivation of DEP model • Link to density • Implicit structuring of airspace • Extend DEP model to take into account effect of (explicit) airspace structure Introduction - Previous Research - Alternate DEP Model - Hypothesis - Capacity Measurement - Conclusions

47. Explicit Airspace Structure # Zones Tubes Full Mix Four Airspace Concepts of Increasing Structure Layers 23 June Hall 1 13:40 #[E. Sunil et al 2016] Introduction - Previous Research - Alternate DEP Model - Hypothesis - Capacity Measurement - Conclusions

48. Thankyou For Your Attention! [e.sunil@tudelft.nl] [https://www.researchgate.net/profile/Emmanuel_Sunil]