1. ADD Validation in NUP2Slide 1 AIRCRAFT DERIVED DATA FOR MORE EFFICIENT ATM OPERATIONS The validation work of NUP II ADD TT Costas TAMVACLIS EUROCONTROL Exp. Centre, Paris, France Nick McFARLANE HELIOS Technology Ltd, Surrey, UK Billy JOSEFSSON LFV (Swedish ANS), Norrköping, Sweden ASAS TN2 Workshop, Sept 26-28, 2005

2. ADD Validation in NUP2Slide 2 Aircraft Derived Data (ADD) What is it, what can it be? ADD and operational use ADD work in NUP II The case of Arlanda RNAV Approaches Current status Conclusions

3. ADD Validation in NUP2Slide 3 What is ADD? ADD is a surveillance application in which avionics data are transmitted from the aircraft to the ground, and possibly other aircraft Reported parameters: Aircraft identification/equipage/equipment status Aircraft configuration flap settings, de-icing etc. Current state measurements, 3-D position, bank angle, ground/airspeed vectors, meteo, weight etc Pilot ‘set’ parameters or targets (short term intent), selected altitude, heading, airspeed and next waypoints Avionics flight path data/calculations, intermediate waypoints and estimated times of arrival (ETAs) The supplied data may be displayed to the Air Traffic Controller, and/or used in ground processing functions and decision support tools.

4. ADD Validation in NUP2Slide 4 ADD Operational Use Controller Access Parameters (CAP) For display to the ATCO Improved Tracking Up to date a/c characteristics More accurate state information Controller Decision Support Tools MTCD, AMAN, MSP Benefit from more accurate trajectory prediction Conformance Monitoring Improved detection of deviations Fewer false alerts Safety Nets Detection of flight level busts Fewer false alerts

5. ADD Validation in NUP2Slide 5 Benefits of ADD to TP ADD ParameterUseBenefit  3D position  speed vectors  vertical rate  roll angle/turn rate  meteo data ADD enhanced tracking and conformance monitoring systems; provide inputs to the TP More accurate inputs to short look- ahead (< 2 min) predictions More frequent and accurate triggers for trajectory recalculation Aircraft weight Aircraft configuration Used in aircraft performance modelingMore accurate climb and descent profile predictions Short term intentConstraints used in climb, descent and turn prediction More accurate turn and climb/ descent profile predictions  Aircraft intent  Top of climb  Top of descent Update the system flight plan on which trajectory prediction is based. More accurate lateral and vertical trajectory estimates Aircraft reported ETAsUpdate or replace ETAs predicted by the ground TP. More accurate ETA estimates

6. ADD Validation in NUP2Slide 6 ADD Validation in NUP II ADD OSED ver 2.7 published ops environment and applicable procedures ADD Validation plan published methodology and required activities for the most promising applications Application selected for validation: Support of “environmentally friendly” RNAV approach procedures at Arlanda Airport Require sequencing and monitoring tools demanding high accuracy trajectory predictions TP accuracy could be improved significantly with ADD

7. ADD Validation in NUP2Slide 7 Arlanda Approaches Current final approach procedures pose significant noise and pollution problems to heavily populated areas. especially for the new runway 01R Legal conditions for using 01R necessitate alternative approach procedures possibly curved RNAV/CDA The new RNAV procedures must ensure safety and maintain current air traffic capacity levels. including support for non equipped traffic

8. ADD Validation in NUP2Slide 8 Validation Exercise Objective A workshop with Arlanda controllers and navigation experts defined suitable approach procedures and decision support tools. These procedures and tools must be assessed to evaluate safety, quantify the achievable air traffic capacity, and establish tool feasibility depends on achievable TP accuracy Initial Objective for ADD validation under NUP II: Determine the achievable TP accuracy though the use of ADD parameters Arlanda RNAV approach validation will be pursued beyond NUP II

9. ADD Validation in NUP2Slide 9 Airport Configuration Arlanda airport has three runways: two parallel runways 01L-19R and 01R-19L converging runway 08-26 located north of 01R Runway usage depends on wind direction and also on peak or off- peak situation Presently segregated operations are used for the two parallel runways. In the future 01L and 01R will be used in mixed mode during peak hours in order to increase capacity

10. ADD Validation in NUP2Slide 10 Current O1R Approaches 01R STAR defined to TEB from where radar vectoring is performed. A/C on STAR do not interfere with other TMA sectors. Depending on traffic situation A/C may be vectored after passing IAF or earlier A B C D E

11. ADD Validation in NUP2Slide 11 Example of curved RNAV Approach RNAV-based ‘S’ turn (two RF turns) manoeuvre before intercepting the ILS. The ‘S’ turn enables avoidance of an environmentally sensitive area. Such an approach would be suitable for RNP 0.3 RNAV equipped aircraft. Issues: safety of independent approaches missed turns merging of straight-in and curved RNAV approaches equipped and non equipped a/c

12. ADD Validation in NUP2Slide 12 Tested curved RNAV procedure

13. ADD Validation in NUP2Slide 13 Merging of mixed traffic A procedure needed to merge the straight-in and curved RNAV traffic approaching 01R The Arlanda workshop recommended: traffic sequencing prior to the split between the two 01R approach branches, AND provision of speed advisories to the controller, OR monitoring tool providing real time visual feedback of merge point arrival spacing Both solutions require highly accurate trajectory prediction need to determine TP accuracy required, and whether this accuracy can be achieved with ADD (and which ADD parameters)

14. ADD Validation in NUP2Slide 14 Current status of validation Simulations of 01R straight-in and curved RNAV approaches with a Boeing 737 cockpit simulator capable of generating ADD applying different weather conditions TP predictions generated from recorded data to measure TP look-ahead accuracy with and without ADD and different subsets of ADD a/c weight, air/ground speed vectors, meteo, autopilot settings, TCPs, GPS position A flight trial is planned (for October 05) to validate the results of the simulations

15. ADD Validation in NUP2Slide 15 Conclusions ADD offer many potential benefits see NUP2 ADD OSED benefits to DST occur primarily through TP accuracy improvements ADD benefit validation is feasible only case by case. The particular case of Arlanda was chosen because it requires high TP accuracy, and may be applicable to many other airports validation is still ongoing (until Dec. 05) will need to be continued beyond NUP II to evaluate impact on RNAV DST and hence controller acceptability and airport capacity

16. ADD Validation in NUP2Slide 16 ADD The link between aircraft and ATM Thank You!

17. ADD Validation in NUP2Slide 17 Example of FMS supplied data ARINC labelNameUnits 001Waypoint 056ETAHours / mins / 0.1 mins 075Gross WeightLbs 103FMC AirspeedKnots 213Static Air TemperatureDegrees C 233-236Flight numberASCII characters 310LatitudeDegrees 311LongitudeDegrees 312Ground speedKnots 315Wind speedKnots 316Wind directionDegrees 321Flight path angleDegrees

18. ADD Validation in NUP2Slide 18 ADD Downlink mechanisms ADS-B - 1090MHz Ext. Squitter - VDL-4 - UAT Enhanced Mode S radar ADS-C ACARS

19. ADD Validation in NUP2Slide 19 Sources of TP Errors Weather forecast uncertainties Turn dynamics Aircraft performance modelling fidelity i.e. simplifications, omissions and uncertainty in the mathematical models used to estimate the trajectory Erroneous assumptions on aircraft characteristics These vary dynamically (for example aircraft weight) but are usually assigned values derived from flight plan data and/or aircraft performance databases Tracking and flight mode errors Pilot and controller intent uncertainties

20. ADD Validation in NUP2Slide 20 Sources of TP Errors Weather forecast uncertainties Turn dynamics Aircraft performance modelling fidelity i.e. simplifications, omissions and uncertainty in the mathematical models used to estimate the trajectory Erroneous assumptions on aircraft characteristics These vary dynamically (for example aircraft weight) but are usually assigned values derived from flight plan data and/or aircraft performance databases Tracking and flight mode errors Pilot and controller intent uncertainties ADD can reduce most of these errors!

21. ADD Validation in NUP2Slide 21 Operational Benefits from ADD 1/2 ICAO adopted 7 conceptual changes at ANConf 11, 2003 4 out of 7 are strongly linked to ADD -traffic synchronization -demand and capacity balancing -conflict management -airspace user operations Benefits, how? -Increased predictability -Increased quality of data -Enriched ATM data is made avilable

22. ADD Validation in NUP2Slide 22 Operational Benefits from ADD 2/2 Safety Strategic and tactical planning i.e. MSP, MTCD Arrival management Flight time spent in holding patterns Optimization of airport resources Collaborative decision making i.e. prioritisation Fleet management