Nationaal Lucht- en Ruimtevaartlaboratorium National Aerospace Laboratory NLR DXXX-1A AI Planning at airports:Departure Management PLANET Industry Day Charles University Prague 26 May 2003 H.H. (Henk) Hesselink Group leader AI and Airport Decision Support Systems

Nationaal Lucht- en Ruimtevaartlaboratorium National Aerospace Laboratory NLR DXXX-2A Today l Introduction NLR l Planning at airports l Departure management - how can AI planning help? l Departure sequencing - details l Results so far and future

Nationaal Lucht- en Ruimtevaartlaboratorium National Aerospace Laboratory NLR DXXX-3A National Aerospace Laboratory (NLR) l NLR is a non-profit foundation since 1937/1919 l NLR provides technical and scientific contributions to activities in aerospace related areas l NLR will independently serve public and private organisations

Nationaal Lucht- en Ruimtevaartlaboratorium National Aerospace Laboratory NLR DXXX-4A Division of Activities into Categories Supported l Civil aerospace: 65%- Military aerospace: 35% l Aeronautics: 85%- Space: 15% l Operations: 60%- Development: 40% l (non-aerospace: < 2%) l Turn over: 150 million hfl.

Nationaal Lucht- en Ruimtevaartlaboratorium National Aerospace Laboratory NLR DXXX-5A Facilities l Large Wind Tunnels (2 low speed, 2 transonic, 1 supersonic, 50% shared in DNW) l Simulators (flight, air traffic control, tower) l Aircraft (Fairchild Metro II, Cessna Citation II) l environments (supercomputer, network, middleware)

Nationaal Lucht- en Ruimtevaartlaboratorium National Aerospace Laboratory NLR DXXX-6A Planning at airports Why do we need planning and what is the most promising step at this moment: departure management

Nationaal Lucht- en Ruimtevaartlaboratorium National Aerospace Laboratory NLR DXXX-7A Planning, the basis l Planning has been the subject of many projects (a.o. military) l Planning in en-route (during flight) is examined –Free routing / autonomous pilot is a concept where the pilot flies his route without intervening with air traffic control - this cannot work without planning l Planning for arrival traffic (still flying) is being implemented at several airports now –Arrival management => Planning at airports is a next step

Nationaal Lucht- en Ruimtevaartlaboratorium National Aerospace Laboratory NLR DXXX-8A ATM Planning: the Problem

Nationaal Lucht- en Ruimtevaartlaboratorium National Aerospace Laboratory NLR DXXX-9A Each airport is different but the same

Nationaal Lucht- en Ruimtevaartlaboratorium National Aerospace Laboratory NLR DXXX-10A Planning decisions to be taken... Apron start upTaxiway crossing Runway holding Intersection take-off Deicing area Left or right track

Nationaal Lucht- en Ruimtevaartlaboratorium National Aerospace Laboratory NLR DXXX-11A Current airport planners l Airport planner 1: pre-flight controller l Responsible for giving clearances and information before the aircraft actually starts moving l Gives SID (= departure route) l Co-ordinates with CFMU (European co-ordinated slot time, central agency in Brussels) l Main problem: communication overload

Nationaal Lucht- en Ruimtevaartlaboratorium National Aerospace Laboratory NLR DXXX-12A Current airport planners l Airport planner - 2: ground controller l Responsible for movements over the taxiways of the airport l Gives taxiing routes l Merges inbound and outbound traffic l Establishes departure sequences l Assesses runway and/or apron congestion to avoid taxiway congestion (use of holdings and parkings)

Nationaal Lucht- en Ruimtevaartlaboratorium National Aerospace Laboratory NLR DXXX-13A Current airport planners l Airport planner - 3: tower controller l Responsible for traffic at runways l Usually one runway per tower controller l Segregated mode vs. mixed mode operations l Large aircraft separation necessary because of wake vortex and speed differences

Nationaal Lucht- en Ruimtevaartlaboratorium National Aerospace Laboratory NLR DXXX-14A Current airport planners l Airport planner - 4: approach controller l Responsible for the airspace around the airport l Sequences arrival traffic l Uses STARs (Standard Arrival Routes) and stacks l Takes care of dependencies between runways (e.g. crossing runways or converging runways), always aware of overshoots or missed approaches l Determines the runway capacity

Nationaal Lucht- en Ruimtevaartlaboratorium National Aerospace Laboratory NLR DXXX-15A Current airport planners l Airport planner - 5: supervisor l Responsible for the flow of traffic l Decides on runway usage l Assesses meteo and decides on airport acceptance rate (per hour) - information will be send to Brussels (CFMU) l Co-ordinates work of other controllers, assesses their workload and decides on division of work over 1 to 10 controllers

Nationaal Lucht- en Ruimtevaartlaboratorium National Aerospace Laboratory NLR DXXX-16A Departure Management How can AI Planning Help?

Nationaal Lucht- en Ruimtevaartlaboratorium National Aerospace Laboratory NLR DXXX-17A Departure sequencing: model

Nationaal Lucht- en Ruimtevaartlaboratorium National Aerospace Laboratory NLR DXXX-18A Departure Sequencing Problem l Sequencing aircraft at the available runways l Computer assistance to the controller team in the control tower l Co-operate with other planners l Planning will be performed before the aircraft starts moving ( minutes in advance). Tool provides sequences on an optimal basis, in stead of (smart) first-come-first-served

Nationaal Lucht- en Ruimtevaartlaboratorium National Aerospace Laboratory NLR DXXX-19A What variables must be planned? runway SID structure 2 min. 5 min. exit holding A * runway assignment runway holdingA 2 min. 5 min. exit * intersection take-off * time (sequences) * SID allocation

Nationaal Lucht- en Ruimtevaartlaboratorium National Aerospace Laboratory NLR DXXX-20A NLR departure sequencer The details of constraint reasoning

Nationaal Lucht- en Ruimtevaartlaboratorium National Aerospace Laboratory NLR DXXX-21A What is planning l Planning is the preparation of actions (movements) in the broadest sense of the word –setting a goal –determining actions to achieve this goal –sequencing these actions l It takes into account the current situation, available resources, changing information, … l Many constraints

Nationaal Lucht- en Ruimtevaartlaboratorium National Aerospace Laboratory NLR DXXX-22A Constraints l Some constraints are hard (CFMU, wake vortex,..) l Some constraints are soft (distribution, pilot wishes,..) l Constraints differ per airport l Constraints differ per situation => We need an implementation that follows all rules (regulations) but still provides some flexibility => AI Planning: constraint satisfaction with optimisation

Nationaal Lucht- en Ruimtevaartlaboratorium National Aerospace Laboratory NLR DXXX-23A Constraint Satisfaction S E N D M O R E + M O N E Y S = [0,1,2,3,4,5,6,7,8,9] E = [0,1,2,3,4,5,6,7,8,9] N = [0,1,2,3,4,5,6,7,8,9] D = [0,1,2,3,4,5,6,7,8,9] M = [0,1,2,3,4,5,6,7,8,9] O = [0,1,2,3,4,5,6,7,8,9] R = [0,1,2,3,4,5,6,7,8,9] Y = [0,1,2,3,4,5,6,7,8,9] C 1 C 2 C 3 C4C4 C = [0, 1] _ _________________ -- C 2 + S + M > 10 etc...

Nationaal Lucht- en Ruimtevaartlaboratorium National Aerospace Laboratory NLR DXXX-24A Departure seq.: constraint satisfaction l Departure slots can be represented as F1 runway = [16L, 16R, 34L, 34R, 07, 25] F1 time = [4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19] F1 SID = [ELBA5A, ELBA5B, ELBA5C] F2 runway = [16L, 16R, 34L, 34R, 07, 25] F2 time = [4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19] F2 SID = [ELBA5A, ELBA5B, ELBA5C] l Constraints: e.g. 3 min. separation between heavy - light: For F1 <> F2 and Runway (F1 = F2) and (Time(F1) Weight(F2)) Conclude Time(F1) + 3 <= Time (F2)

Nationaal Lucht- en Ruimtevaartlaboratorium National Aerospace Laboratory NLR DXXX-25A Departure Sequencing Problem l Runway assignment –Environmental constraints –Meteo conditions –Different runway entry points (CAVOK) l Separation –Wake vortex –Speed l Distribution –Initial climb routes/SIDs –TMA exit point acceptance rate

Nationaal Lucht- en Ruimtevaartlaboratorium National Aerospace Laboratory NLR DXXX-26A Departure Sequencing Problem l Time –Achieve CFMU time constraints (flow restrictions) –Give preference to late aircraft l Optimisation –Minimise runway throughput –Make efficient use of available airspace –Depart as early as possible –Provide flexibility l Controller/pilot –Controller makes decisions, machine supports –Pilot may have preferences

Nationaal Lucht- en Ruimtevaartlaboratorium National Aerospace Laboratory NLR DXXX-27A Departure sequencing: HMIs

Nationaal Lucht- en Ruimtevaartlaboratorium National Aerospace Laboratory NLR DXXX-28A Trial implementation at Prague airport (Integrated in the NOVA system)

Nationaal Lucht- en Ruimtevaartlaboratorium National Aerospace Laboratory NLR DXXX-29A Results so far and future work Where do we stand and what do we expect from the future

Nationaal Lucht- en Ruimtevaartlaboratorium National Aerospace Laboratory NLR DXXX-30A Departure sequencing: concept Departure sequence Intersection take-off Taxiway routing Co-ordination Apron management Co-ordination Start-up Push back De-icing Runway allocation Wake vortex Speed Flow restrictions CFMU slots SID usage

Nationaal Lucht- en Ruimtevaartlaboratorium National Aerospace Laboratory NLR DXXX-31A Controller support in planning l With the provision of a departure management function, we will be able to: l Enable a better knowledge of the current and future situation (situation awareness) l Provide continuous optimal capacity l Provide the controller a new challenging operational task –make strategic decisions on departure management –provide advanced guidance –increase safety with new complex procedural demands

Nationaal Lucht- en Ruimtevaartlaboratorium National Aerospace Laboratory NLR DXXX-32A Results so far l Implementation in C ++, connected to CORBA in A-SMGCS simulator; core scheduler build in ILOG l Off-line DMAN evaluations at Rome-Fiumicino and Paris- Orly ( ) l On-line DMAN tests at Prague and Hamburg ( ) l Simulator trials for Frankfurt (2002) (Tower simulator) l Current activities: –Connection to pilot (CDM) –New trials with controllers in the simulator

Nationaal Lucht- en Ruimtevaartlaboratorium National Aerospace Laboratory NLR DXXX-33A Results so far l In a new set up, we are investigating planning & negotiation algorithms: intelligent agents l Several contributions to Advanced Airport Technology course at the Institute of Air Navigation Services (Eurocontrol Luxembourg) –Departure management course –NLR Demonstration is running at IANS l Several papers have been published

Nationaal Lucht- en Ruimtevaartlaboratorium National Aerospace Laboratory NLR DXXX-34A Planning and co-ordination

Nationaal Lucht- en Ruimtevaartlaboratorium National Aerospace Laboratory NLR DXXX-35A Some results from operational trials l Prague evaluations (27 May - 7 June 2002) Hamburg evaluations ( September 2002) l DMAN resulted in a smoother traffic flow for runway occupancy (results are obtained from simulator trials) DMAN No DMAN

Nationaal Lucht- en Ruimtevaartlaboratorium National Aerospace Laboratory NLR DXXX-36A Future of airport planning l Planning is a novel concept to be supported l Forces controllers to evaluate start-up and push-back requests and gives additional information (situational awareness) l First efficiency benefit have been proven. New demands will arise for e.g. environmental monitoring, in which planning can provide great help l Changing operational procedures is not always appreciated; we slightly started to explore the possibility l Controller wants to be in command

Nationaal Lucht- en Ruimtevaartlaboratorium National Aerospace Laboratory NLR DXXX-37A The result: