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AI Planning, Waiting for the Results? H.H. Hesselink (hessel@nlr.nl) R.R. Seljée (seljee@nlr.nl)

AI Planning, Waiting for the Results? H.H. Hesselink (hessel@nlr.nl) R.R. Seljée (seljee@nlr.nl). 2nd Gap-Bridging Seminar PLANSIG 2002 TU Delft 21 November 2002. NLR. NLR is a non-profit foundation since 1937/1919

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AI Planning, Waiting for the Results? H.H. Hesselink (hessel@nlr.nl) R.R. Seljée (seljee@nlr.nl)

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  1. AI Planning, Waiting for the Results? H.H. Hesselink (hessel@nlr.nl) R.R. Seljée (seljee@nlr.nl) 2nd Gap-Bridging Seminar PLANSIG 2002 TU Delft 21 November 2002

  2. NLR • NLR is a non-profit foundation since 1937/1919 • NLR provides technical and scientific contributions to activities in aerospace related areas • NLR will independently serve public and private organisations

  3. NLR - Civil aerospace: 65% - Military aerospace: 35% - Aeronautics: 85% - Space: 15% - Operations: 60% - Development: 40% (non-aerospace: < 2%) Turn over: 70 MEuro.

  4. NLR • Large Wind Tunnels (2 low speed, 2 transonic, 1 supersonic, 50% shared in DNW) • Simulators (flight, air traffic control, tower) • Aircraft (Fairchild Metro II, Cessna Citation II) • Computing environments (supercomputer, Network, middleware)

  5. NLR • NLR undertakes studies and implementations for Schiphol • Safety cases • Policy studies • Simulator trials • Implementations • Co-operation with Dutch Industry (HITT) • TCM (Taxiway Collision Monitoring) • Triple-I: Intelligence Instead of Infrastructure • Co-operation with Eurocontrol

  6. Projects with AI Planning and Scheduling • MADS:Departure Planning Decision Support at Airports • Runway Use Advisory and Inspection Systems: BGAS & BGCS • Tools for Route Planning and Manoeuvre Planning • Crew Assistant is a decision support system for a pilot • Mission Support System Campal (MSS/C) is a powerful tool • for military mission planning Planning in Air Traffic Management (ATM): the Big Picture

  7. ATM Planning: the Problem

  8. Artificial Intelligence and Planning • The traffic increase gives the operational need • Problem not recognised by controllers (the end users) • Academia wants to experiment new techniques • Academia wants complex methods for operator modelling • Side effects: • Establishing better collaboration • Acceptance of new technology in an organisation • Studying other solutions, • e.g. use trains in case of Air Traffic Growth

  9. The Problem: Division of ATM • Arrival management • Departure management • Surface movement • Stand allocation • Flight management

  10. The Problem: Many Actors • Many actors involved: • Airlines/AOC • Pilots • Air Traffic Controllers • En-route ATC • Approach ATC • ATC Departure/Tower • Other Airports ATC • Apron Controllers • Ground Movement Controllers • CFMU • Meteo Service Providers

  11. Each airport is different but the same

  12. aircraft surveillance Guidance control planning Airport traffic management control loop

  13. Collaborate Decision Making (CDM)

  14. How from FCFS to planning • RESEARCH • planning • more advanced technology • talk to operators • increase efficiency • OPERATORS • first heard first served • conservative (safety) • no time / no interest • one aircraft vs cowboys The GAP

  15. How to bridge this gap? • Start with foundations of the bridge • Finances • Interest from operators • prototypes

  16. Foundation: finances • Contributions from research (NLR itself) • Contributions from subsidiary projects (EC) • Contributions from Eurocontrol • Where is industry to subsidise this work?

  17. Foundation: interest • Make operators aware of their problem • Make operators aware of solutions • Convince operators that they will not be replaced (by automation) • Convince operators of new challenges • Convince airport managers of the need

  18. Foundation: prototypes • Build realistic prototypes • Give operators the possibility to interact • Large simulators, with controller-n-the-loop

  19. The bridge • Integration projects • Demonstrations • Emotional response to new things must be broken => give the operator a “positive feeling” about our work

  20. Where is industry? • Industry is waiting for results (to sell) • Operators are waiting (if at all) ...

  21. NLR work to demonstrate to planners • Introduce a planning and scheduling function at airports for scheduling traffic and assist traffic controllers • Evaluate the use and benefit of the tool • We build a planner with constraint reasoning (ILOG Solver and Scheduler) • Symbolic representation of the problem based on the “flight”abject • Constraints: separation, meteo, runway length, traffic distribution, ...

  22. A 2 min. SID structure 5 min. runway holding A 2 min. runway exit 5 min. Simplified model • runway assignment • intersection take-off • take-off time (sequences) • SID allocation

  23. _ X Active Departures -5 0 +5 +15 +10 CALLSIGN STND CTOT EOBT TYPE/W DEST RWY SID SSR ALERT TAXIROUTE REMARK STAT CLR TVS338 N26 1947 B734/M LEPA 24 BANAS2A 0234 BCS916 N5 1945 1940 B722/M EDDF 24 KADNO 0237 TAR8861 N22 1940 1928 B732/M DTTA 31 KADNO 0344 TAR229 N27 1930 1924 A30B/M DTTA 31 RAK 0332 FFR8105 N1 1920 1915 B733/M LDDU 24 BANAS2A 0232 CSA270 N9 1916 1909 B735/M HECA 24 RATIS 0331 NO PUSH CSA978 N20 1910 1904 AT72/M LZKZ 24 RATIS 0336 J-H-B Delete Edit TWR/APP HMI

  24. The result of our work • Operators start to understand the idea of planning • Operators are willing to express their knowledge • Industry has been invited to participate and show their operational products (radars and HMIs) • Industry was invited for a “picnic day”=> We brought industry in contact with end users

  25. And further ... • More experiments in our tower simulator • More demonstrations in real control towers • Bring results to airport decision makers (presentations) • Bring results to industry (software and design) … and sell it!

  26. Questions ?

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