June 29, 2018...8 Intrinsic Airspace Safety Intrinsic safety is the safety that is provided...

11

June 29, 2018

Emmanuel Sunil, Ólafur Þórðarson, Joost Ellerbroek and Jacco Hoekstra

2

Outline

Introduction

Baseline Analytical Model

Fast-Time Simulation Experiments

Results and Numerically Adjusted Models

Conclusions

3

1.Introduction

4

ATM in Fast-Time Simulations

5

Metropolis Project

Tubes

4 Constraints

• X Position

• Y Position

• Altitude

• Speed

Zones

2 Constraints

• X Position

• Y Position

Layers

1 Constraint

• Altitude

Unstructured

0 Constraints

Four Airspace Concepts of Increasing Structure

Compared Using Fast-Time Simulations

6

Pros and Cons of Simulations

Pros Cons

High-level system dynamics

Can be very realistic

Analyze different conditions

Time consuming

Results can be qualitative

Difficult to generalize results

7

Conflict Count Models

Inst. Conflict Count =

Number of combinations of 2 aircraft

Conflict probability between any 2 aircraft

X

8

Intrinsic Airspace Safety

Intrinsic safety is the safety that is provided exclusively by the constraints imposed on traffic

motion by an airspace design

Tubes

4 Constraints

• X Position

• Y Position

• Altitude

• Speed

Zones

2 Constraints

• X Position

• Y Position

Layers

1 Constraint

• Altitude

Unstructured

0 Constraints

9

Conflict Count Models

Inst. Conflict Count =

Number of combinations of 2 aircraft

Conflict probability between any 2 aircraft

X

10

What is a Traffic Scenario?

1. Speed

2. Heading

3. Altitude

4. Density/Spatial

A traffic scenario describes the distributions of aircraft:

11

Traffic Scenario Assumptions

1. Speed is equal for all aircraft

2. Heading distribution is uniform

3. Altitude distribution is uniform

4. Density/spatial distribution is uniform

How accurate are these models for more realistic traffic scenarios?

Ideal Traffic Scenario

12

Research Goals

1. Study the effect of traffic scenario assumptions on the accuracy of analytical conflict count models for more realistic traffic scenarios

– Unstructured airspace used as a case study

2. Derive and test ‘model adjustments’ to generalize the models for all traffic scenarios

13

2.Baseline Analytical Model

14

Intrusions vs. Conflicts

2𝑆ℎ

Intrusion Conflict

15

Conflict Count Model for

Unstructured Airspace

Inst. Conflict Count =

Number of combinations of 2 aircraft

Conflict probability between any 2 aircraft

X

16

Number of Combinations of 2 A/C

1

3

24 5 6

17

Average Conflict Probability

𝑝 =𝐵𝑐

𝐵𝑡𝑜𝑡𝑎𝑙

18

Average Conflict Probability

19

Traffic Scenario Assumptions

Assumes uniform altitude and density/spatial distributions of traffic

𝑝 =𝐵𝑐

𝐵𝑡𝑜𝑡𝑎𝑙

20

Traffic Scenario Assumptions

Assumes equal ground speed and uniform heading distribution of traffic

21

Traffic Scenario Assumptions

1. Speed is equal for all aircraft

2. Heading distribution is uniform

3. Altitude distribution is uniform

4. Density/spatial distribution is uniform

Ideal Traffic Scenario

For Unstructured Airspace, all 4 assumptions affect the average conflict probability between any two aircraft

22

3.Fast-Time Simulation Experiments

23

BlueSky Open ATM Simulator

https://github.com/ProfHoekstra/bluesky

24

4 Assumptions – 4 Experiments

1. Ground-Speed Experiment

2. Heading Experiment

3. Altitude Experiment

4. Spatial Experiment

Traffic Scenarios

• 5 Densities (5-100 a/c per 10,000 NM2)

• 5 Repetitions

25

Ground Speed Experiment

Baseline analytical model

Different mix of aircraft types

26

Heading Experiment

Uniform Normal

Bimodal Ranged-Uniform

27

Altitude Experiment

Baseline analytical model

Traffic in upper airspace for

fuel efficiency

One preferreddestination

Two preferreddestinations

28

Spatial Experiment

Uniform

Hot Spot 1 Hot Spot 2

29

4.Results and Numerically Adjusted

Models

30

Model Accuracy Measurement

Analytical Model for Ideal Traffic Scenario

No. Inst Conflicts = Model ∙ k

𝑘 = 1 100% accuracy

𝑘 < 1 Overestimation

𝑘 > 1 Underestimation

k = 1.024 (97.6%)

31

Ground Speed Experiment

No substantial effect of ground speed distribution on safety for Unstructured Airspace

32

Ground Speed Adjustment

33

Ground Speed Adjustment

34

Ground Speed Experiment

35

Heading Experiment

Heading distribution can cause the analytical model to over-estimate conflict counts

36

Heading Adjustment

37

Heading Adjustment

38

Heading Experiment

39

Altitude Experiment

Altitude distribution can cause the analytical model to significantly under-estimate conflict counts

40

Altitude Adjustment

A/C j in vertical range of A/C i

Altitude spread of all A/C

41

Altitude Experiment

42

Spatial Experiment

Spatial distribution can cause the analytical model to significantly under-estimate conflict counts

43

Spatial Adjustment

𝐶𝑡𝑜𝑡𝑎𝑙 = 𝐶𝑎𝑟𝑒𝑎1 + 𝐶𝑎𝑟𝑒𝑎2 + 𝐶𝑎𝑟𝑒𝑎1,2

Area 2

Area 1

44

Spatial Experiment

45

5.Conclusions

46

Conclusions

• Analytical model very accurate for ideal traffic scenario

• Conflict probability was incorrectly predicted by analytical model for non-uniform heading, altitude and spatial distributions.

• Spatial distribution of traffic led to the largest negative impact on the accuracy of the analytical model

• Ground-speed distribution did not affect analytical model accuracy

• Numerical model adjustments increased model accuracy for non-ideal conditions

47

Conclusions

• Adjusted conflict count models:

– Understand the relationships between the factors affecting airspace safety

– Tool for practical airspace design applications

• Future work will extend model adjustments for layered and other airspace designs

48

Thank You For Your Attention!

[e.sunil@tudelft.nl][https://www.researchgate.net/profile/Emmanuel_Sunil]