1. Aena Zilina, 23.11.04 Zilina, 22-24.11.04 How to improve Airport Efficiency by means of CDM: LEONARDO Linking Existing ON ground, ARrival and Departure Operations Patricia Pina ppina@aena.es Maria Mas mmas@aena.es

2. Zilina, 23.11.04 Contents  Scope & Approach  The System  Trials results  Arrival predictability  Off-Block predictability  Departure predictability  CFMU slot predictability  Conclusions

3. Zilina, 23.11.04 Scope of LEONARDO  Problem: Lack of efficiency  Individual optimisation of airport processes  Existing information not available for all actors  Solution: Integrate existing planning tools for:  Arrival management  Departure management  Ground operations management INTEGRATION LAYER AIRLINES AIRPORT OPERATIONS ARRIVAL PROCESS FLOW CONTROL DEPARTURE PROCESS GMC GATE ALLOCATION

4. Zilina, 23.11.04 LEONARDO Approach  3 different levels of integration  Information sharing  Cooperation - Improvements in planning estimates  Negotiation among actors  2 different validation techniques  Shadow mode trials  Real time simulations  2 different testing airports  Barajas  Charles de Gaulle

5. Zilina, 23.11.04 The System

6. Zilina, 23.11.04 Human-Machine Interface

7. Zilina, 23.11.04 Arrival Estimates SLDT ELDT SIBT EIBT Taxitime MIBT AMANSMANCDM LEONARDO MLDT ACARS ALDT AIBT

8. Zilina, 23.11.04 In-Block Predictability MINUTES Average |EIBT airport - AIBT| Average |EIBT airline - AIBT| Average |MIBT - AIBT| Deicing Area G9 G6 G17 G18 G19 G3 G1 G18 TWR G1G3G6G9 G14 G17 G18 G19 TOTAL 12:58 10:05 11:31 0:00 8:38 5:46 4:19 2:53 7:12 1:26 MIBT Mean Absolute Error G14 36L 33

9. Zilina, 23.11.04 Turn Around Estimates TOBT Turn-Around Time CDMAirline LEONARDO MIBT ACARS AIBT ATOT SOBT EOBT

10. Zilina, 23.11.04 Off-block predictability  Better In-block time prediction, thus better TOBT prediction  Improvement of TOBT Predictability due to the info shared by the airlines with the CDM system.  24 % error decrease when considering delay messages from the airline

11. Zilina, 23.11.04 Departure Estimates SOBT EOBT STOT ETOT Taxitime MTOT CDMSMANDMAN LEONARDO TOBT ACARS AOBT ATOT

12. Zilina, 23.11.04 Take-Off predictability  Improvement of ETOT Predictability due to a better TOBT and taxiing time.  DMAN calculates the optimum departure sequence: MTOT ERROR AS A FUNCTION OF % EGOP

13. Zilina, 23.11.04 Probability of slot alarm to be reliable  Statistical simulation of the Alarm prediction based on taxiing time distribution  Measurement of discrepancies between simulated alarms and slot compliance

14. Zilina, 23.11.04 LEONARDO Results In-block Predictability  CDM has positive effect on efficiency, further improvement possible Off-block Predictability Up to 80% improvementUp to 50% improvement Take-off Predictability Up to 50% improvement

15. Zilina, 23.11.04 Leonardo Conclusion  CDM makes sense  Experiments in the three sites confirm us the same tendency:  Improvement in predictability of operations  Better management of existing resources (stands, handling equipment, runway)  Improvement of decision-making processes  The R&D results are available and stakeholders should use them: http://leonardo.aena.es

16. Zilina, 23.11.04 Future Work  Implement collaborative processes with CFMU  Inclusion of actors priorities and negotiation  Creation of a network: integrate tools at origin and destination airports CFMU

17. Zilina, 23.11.04 THANK YOU FOR YOUR ATTENTION