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4th EUROCONTROL Innovative Research workshopDay II – December 2005, the 7th

Performance Parameters Of Speed Control

&Potential Of Lateral Offset

Rüdiger EhrmanntrautEUROCONTROL Experimental Centre (EEC)

Brétigny sur Orge, France

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Strategic Traffic Organisation– Concept Elements

Strategic Traffic Organisation

CE1Complexity Prediction

CE2Multi Sector

Traffic Organisation

CE3Functional Airspace

Segregation

CE4Synchronous

Planning

Lateral Offset

Vertical Offset

Speed Control

Contracts

System WideInformation

Management

ConflictGeometries

ConflictDensity

Highways

4D / 3D Tubes

Dynamic Sectors

3DAirways

ClusterOrganisation

Flow and Sequences

Strategic Traffic Organisation

CE1Complexity Prediction

CE2Multi Sector

Traffic Organisation

CE3Functional Airspace

Segregation

CE4Synchronous

Planning

Lateral Offset

Vertical Offset

Speed Control

Contracts

System WideInformation

Management

ConflictGeometries

ConflictDensity

Highways

4D / 3D Tubes

Dynamic Sectors

3DAirways

ClusterOrganisation

Flow and Sequences

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Validation process

Concept definitionConcept element 1: ComplexityConcept element 2: MSPConcept element 3: 3D routes

Fundamental ATM researchWhy this approach?What is it?What benefit?

Capacity, safety, environmentFast time simulation

System DesignHow?

AutomationInformation systemTechnologies

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Simulation Airspace and Traffic Model

RAMS 5.04 Plus5 States scenario (Dowdall 2001)

12 Sep. 1997 =100%150% (~2005)200% (~2010) 300% (?)140 sectors from 24 ATC Karlsruhe, Maastricht and Reims

36 en-route sectors above flight level 245

9. R. Dowdall, 2001, 5 States Fast-Time Simulation, EUROCONTROL Experimental Centre, EEC Report No.361, www.eurocontrol.int/eec/publications.html

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Number of Aircraft per Hour for Three Measured Centres (150% Scenario)

0100200300400500600700800900

00:00

02:00

04:00

06:00

08:00

10:00

12:00

14:00

16:00

18:00

20:00

22:00

KARLSRUHE MAASTRICHT REIMS

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Conflict-Attitudes Per Flightlevel Bands for the 3 Centres

0

50

100

150

200

250

300

190

210

230

250

270

290

310

330

350

370

390

410

Cruise-Cruise Cruise-Attitude Attitude-Attitude

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Aircraft at flight level of entire 1997 scenario

0.0%

2.0%

4.0%

6.0%

8.0%

10.0%

12.0%

10-19

40-49

70-79

100-1

0913

0-139

160-1

6919

0-199

220-2

2925

0-259

280-2

8931

0-319

340-3

4937

0-379

400-4

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Rüdiger EhrmanntrautFrank Jelinek

EUROCONTROL Experimental Centre (EEC)Brétigny sur Orge, France

Performance Parameters Of Speed Control

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Average (cruise) speeds per FL with std.-dev.

0

100

200

300

400

500

600

10-1

9

30-3

9

50-5

9

70-7

9

90-9

9

110-

119

130-

139

150-

159

170-

179

190-

199

210-

219

230-

239

250-

259

270-

279

290-

299

310-

319

330-

339

350-

359

370-

379

390-

399

410-

419

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Aircraft Performance Envelopes

Update with BADA 3.5 (Nuic 2004)More than 100 performance modelsPrecise speed models for 20 aircraft typesOther speed profiles by ICAO class: Heavy, Medium, Light

Limited to 15% from nominal behaviour

A30B Cruise Speed Variance in %

0%

5%

10%

15%

20%

25%

30%

0

200

220

240

260

280

300

320

340

360

380

400

999

Flight Level

3. [12] A. Nuic, 2004, BADA Version 3.5, EUROCONTROL Experimental Centre, www.eurocontrol.fr/projects/bada/

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Conflict and Controller Model

Tactical (TC) ∆LTC = 0 min∆STC = 5NM

Look-ahead parameter ∆L

Maximal Implementation interval ∆R

ac1

ac2

e1 e3

e2

e4

S1

Planner (PC)∆LPC = 15 min∆SPC = 7NM

S2

Separation Buffer ∆S

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Rulebase Logic

Conflict Geometry Analysis

Which a/c to penalise?

Speed Reduction?Speed Increase?

Set Resolution ConstraintsNew speed, times

Reduce penalisedIncrease penalisedReduce favouriteIncrease favourite

Penalise:1. requesting occupied stable FL2. nearer to airport3. inbound and second4. inbound vs outbound5. evolution vs stable6. behind7. below8. in descent9. significantly faster10. about to leave cruise11. still on ground

Set resolution start timeSet resolution stop timeIterate speed

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Uncertainty Model

Uncertainty modeled by higher lateral separationsPlanner separated on 7NM horizontal buffer, 1000 feet verticalPlanner 6% uncertainty per hour = 1.5% in the look-ahead horizon.Radar 0% uncertainty

7 NM5 NM

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Simulation Scenarios

A Conflict Detection only, no resolutions

B Planner resolves speed-onlyRadar is disabled

C Planner resolves vertical-only (+/- 2 RVSM flight levels)Radar is disabled

D Planner resolves speed-onlyRadar resolves speed-only

E Planner resolves speed-onlyRadar resolves horizontal-vectors-only

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Results-Overview

0

2000

4000

6000

8000

10000

12000

14000

16000

A B C D E A B C D E A B C D E A B C D E

100 150 200 300

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Conflicts Unresolved % Resolved Unresolved / Flights

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0

200

400

600

800

1000

1200

-18

-17

-16

-15

-14

-13

-12

-11

-10

- 9 - 8 - 7 - 6 - 5 - 4 - 3 - 2 - 1 + 1 + 2 + 3 + 4 + 5 + 6 + 7 + 8 + 9 +10

+11

+12

+13

+14

+15

+16

+17

100 - B 100 - D 100 - E 150 - B 150 - D 150 - E200 - B 200 - D 200 - E 300 - B 300 - D 300 - E

Speed Adjustment %

# resolved

Results-Distribution of Speed Adjustments

►many small speed adjustments►+ and – unbalance is due to rule base, not to ac performance

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-

1 000

2 000

3 000

4 000

5 000

6 000

7 000

8 000

100 150 200 300 100 150 200 300 100 150 200 300 100 150 200 300B C D E

0%

20%

40%

60%

80%

100%

0 - 10 10 - 30 30 - 90 % resolved 0 - 10 % resolved 10 - 30 % resolved 30 - 90

Results-Encounter Angles and their Resolution Rates

• Other study shows that conflicts almost equally distributed over angle 1°-179°

►More speed resolutions for wide angles• Small angel = 0° and 180°►Climbs and descents can still be

resolved with speed

0 90 180

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Results-Minimal Displacement Distance and their Resolution Rates

40%

50%

60%

70%

80%

90%

1NM 2NM 3NM 4NM 5NM 6NM 7NM

B C D E

►critical conflicts more difficult►safets? The PC-speed-only and the PC-speed-TC-vectors

CPA Distance

Resolution rates

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Results-Conflict Clusters

Cluster: transitive closure of conflicting aircraft in time (anddistance).

Cluster A-B-CIf D in conflict with A, or B, or C, then cluster A-B-C-D

B

C

A

D

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1

10

100

1000

10000

100

150

200

300

100

150

200

300

100

150

200

300

100

150

200

300

100

150

200

300

100

150

200

300

100

150

200

300

100

150

200

300

100

150

200

300

100

150

200

300

CL_1 CL_2 CL_3 CL_4 CL_5 CL_6 CL_7 CL_8 CL_9 CL_10

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

Results-Conflict Clusters Average Sizes

Normal conflict

Cluster size

Resolution ratesLog count

Senario D = planner and radar use speed-onlyCluster = +/- 5 FL and 8 minutes, no distance limitation►Exponential decrease of cluster sizes► Graceful degrading for big clusters

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0%

100%

300%

500%

700%

900%

1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10100 200 300

PC vertical – TC nil

PC speed – TC nil

Results-Number Constraining Aircraft (1)

# constrainingTraffic growth

►vertical and speed resolution differ

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Results-Constraining Aircraft Average Resolution Rates

0%

20%

40%

60%

80%

100%

r 0 r 1 r 2 r 3 r 4 r 5 r 6 r 7 r 8 r 9300

TC speed – PC nil

TC vertical – PC nil

TC speed – PC vector

TC speed – PC speed

• Read: xx % of conflicts with n constraining aircraft could be resolved by TC-PC

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Results-Environmental Parameters for TC speed – PC speed

94%95%96%97%98%99%

100%101%

D D D100 150 200

Fuel CO HC NOx H2O CO2 SO2

► small effect or even positive effect of speed control

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Discussion + Conlcusions

Capacity:►Speed control very high performance►Graceful behaviour for conflict clusters►Graceful behaviour for conflict with many constraining aircraft

Automation with MSP►If MSP function is automated and uses speed control only, then the radar controller is left with

much less conflicts, but with complicated clusters.►Automation: The capacity barrier is the limited airspace - efficient packing and traffic

organisation are requiredSafety►Speed resolutions have good behaviour for critical conflicts►Safety best when planner and radar controller apply different resolutions (orthogonal solutions)►Radar control did not impact the ability of a long-term planner (15 minutes = MSP) to resolved

with speed controlEnvironment►Small speed adaptation often sufficient►No or very little positive impact when applying speed control

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What is Lateral Offset?

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Lateral Offset - Literature

Herndon, A. A., et al., 2003Utilizing RNAV Avionics: Testing Lateral Offset Procedures, MP03W160, The MITRE Corporation, McLean, VA., in proceedings of the 22nd DASC, Indianapolis, Indiana, USA

field trials in Albuquerque and Houston, single centre: 32 aircraftControllers and pilots seem to accept procedure

Herndon, A. A., J. S. DeArmon, J. Spelman, 2004Use Of Lateral/Parallel FMS Procedures And Implementation Issues, MITRE CAASD, in proceedings of the 23rd DASC, Salt Lake City, USA

Minneapolis ARTCC: 15 flightsQuantification of benefits difficult due to small traffic setReconfirms acceptance

Related literature: RNP-RNAV, ICAO SASP

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RAMS Simulation Model

AT (time) TURN RIGHT/LEFT (heading or number of degrees) OFFSET (distance) REJOIN ROUTE ABEAM (location)Start time, time increment, search directionOffset direction: left, rightOffset angelOffset distanceRejoin location: end of sector, end of centre, end of route, top of descent

CDt CSt

aheadlookT −

ttionimplementaLOt −

T∂

→∆T

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Lateral Offset Resolution Model

12

3 4

→∆T

FOR EACH rejoin-location (rule-base driven)FOR flight1 AND flight2 (rule-base driven)

FOR forward-search OR backward-searchFOR EACH offset-distance

FOR EACH offset-directionFOR EACH offset-angle

TRY new trajectory

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Results (1) –Rejoin Rules

Setup 1: offset-distance 5 + n*2 <15 NM, offset angle 30 deg +/- 15Resolution trigger time -15 minutes

0

1000

2000

3000

4000

5000

6000

Y-combi Y-EoC Y-EoR Y-EoS Y-TOD

200

0%

10%

20%

30%

40%

50%

60%

70%

80%

Conflicts Unresolved % Resolved Unresolved / Flights

Year 2010

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Results (2) –Resolution Rates per Encounter Angel and Geometries

Climb-Descent 8%

Climb-Cruise 33%

Desc-Desc 4%

Cruise-Cruise33%

Climb-Climb 6%

Cruise-Desc16%

50%

60%

70%

80%

90%

100%

Clim

b-C

limb

Cru

ise-

Cru

ise

Des

cent

-D

esce

nt

Clim

b-C

ruis

e

Clim

b-D

esce

nt

Cru

ise-

Des

cent

0°-2°/178°-180° 2°-15°/165°-178° 15°-165° all

►best is descent-descent►worst is climb-climb►cruise is insensitive for encounter angle

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Results (3) –Different Offset Anges

56.0%

58.0%

60.0%

62.0%

64.0%

66.0%

68.0%

10 15 20 25 30 35 40 45

Scenrios run each with different offset angleOffset angle = rejoin angle

►Observed optimum at 35 degrees

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Results (4) –Discrete Offset Distance

0

1000

2000

3000

4000

5000

6000

1 x 7NM 2 x 7NM 3 x 7NM 5+n*2<15

200

0%

10%

20%

30%

40%

50%

60%

70%

80%

Conflicts Unresolved Resolutions % Unresolved/Flights %

Resolution with 1, 2, or 3 offset distances in 7 NM intervals►2*7 and 3*7 equal►1*7 worst, but still very high resolution

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Results (5) –Discrete Offset Distance Distribution

1

10

100

1000

10000

-21 -14 -7 0 7 14 21

0 deviation 1 deviation 2 deviations3 deviations 4 deviations

log scale

Resolution with 1offset distances in 7 NM►distributes until +/- 21NM►No aircraft encountered >4 deviations►A 10% rule?►Resolution space still drastically under-utilised

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Results (6) –Uncertainties

40%50%60%70%80%

PC4%

PC6%

PC12%

PC18%

TC4%

TC12%

TC18%

% Resolutions

Conflict detection with 4, 6, 12, or 18% uncertainty►Lateral Offset requires long look-ahead times►Planning Controller PC degrades►Radar Controller TC degrades faster

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Results (7) –Picture Simulation Output

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Found Issues

Syntax needs improvement – proposed clearance can lead to error►Corrected in this study

Syntax needs improvement - clarity on offset distanceWhen aircraft already flying LO get another additional LO clearance

►We propose always absolute distance from initial flight plan

LO direction should be optimised for trajectory

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Discussion (1)

Multi Sector Planner as Conflict Solver:►LO very high performance►LO insensitive for uncertainties►LO low impact on flight efficiency

Complexity Reduction►LO has very high degree-of-order (metric proposed by Ehrmanntraut)

Flow Safety Maximisation►LO safer because conflict

densities reduced►LO safer because of planning

horizon, time to chaos is bigger

ABCABC

DEF

OPR

LMNLMN

RSTRST

GHI

AFR8910 LL290 330 BAW4561

330 AZA1234 335 370

BAW414290

SAB910 ST289 260

AFR745310

DHL1234335 370

LTU114 NE335 370

AF747 330

BAW5944330

UVWUVW

XYZXYZ

S

BS

AS

cdacabC −−

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Lateral Offset Conclusions

►LO very high resolution rates►optimum offset angle 35 degrees►best for cruising en-route traffic►operates well with reduced number of offset distances►operates well under high uncertainties►there are open issues►very useful for a tactical Multi Sector Planner►should improve safety

►is easy and cheap to implement

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Lateral Offset or Speed?

0

2000

4000

6000

8000

10000

12000

14000

16000

LO Speed LO Speed

Traffic 200 = 2010 Traffic 300 = 2025

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

Conflicts Unresolved Resolutions % Unresolved/Flights %

Attention: two models are compared≠►Both perform very well►LO ‘better’ than speed control?

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Summed Up

Both measures very promisingSector capacity booster

To discussQuantify workload and capacity?Operational feasibility to let MSP operate with speed and offset?Uncertainties due to look ahead horizon?

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