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Nationaal Lucht- en RuimtevaartlaboratoriumNational Aerospace Laboratory NLR
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AI Planning at airports:Departure Management
PLANET Industry Day
Charles University
Prague
26 May 2003
H.H. (Henk) HesselinkGroup leader AI and Airport Decision Support Systems
(hessel@nlr.nl)
Nationaal Lucht- en RuimtevaartlaboratoriumNational Aerospace Laboratory NLR
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Today
Introduction NLR
Planning at airports
Departure management - how can AI planning help?
Departure sequencing - details
Results so far and future
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National Aerospace Laboratory (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
NLR
Education– Universities– Technical Colleges
GovernmentMinistries– Transport
– Defence– Environment
Operators
Industrys
– Aircraft– Space– Other, incl.
Electronics,Remote Sensing
– Royal NL Air Force– Royal NL Navy– KLM– Air Traffic Control– Amsterdam Airport
Schiphol
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Division of Activities into Categories Supported
Civil aerospace: 65% - Military aerospace: 35%
Aeronautics: 85% - Space: 15%
Operations: 60% - Development: 40%
(non-aerospace: < 2%)
Turn over: 150 million hfl.
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Facilities 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)
environments (supercomputer, network, middleware)
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Planning at airportsWhy do we need planning and what is the most
promising step at this moment: departure management
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Planning, the basis
Planning has been the subject of many projects (a.o. military)
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
Planning for arrival traffic (still flying) is being implemented at several airports now– Arrival management
=> Planning at airports is a next step
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5
1997 2000
2010 2020
DIVISION DED 4 - 4/11/97
7.0 Mio Flights 8.0 Mio Flights
11.9 Mio Flights 15.8 Mio Flights
Flights 150 or more
Flights 100 to 150
Flights 50 to 100
Traffic Growth
ATM Planning: the Problem
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Each airport is different but the same
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Planning decisions to be taken ...
Apron start upTaxiway crossing
Runway holdingIntersection take-off
Deicing area
Left or right track
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Current airport planners
Airport planner 1: pre-flight controller
Responsible for giving clearances and information before the aircraft actually starts moving
Gives SID (= departure route)
Co-ordinates with CFMU (European co-ordinated slot time, central agency in Brussels)
Main problem: communication overload
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Current airport planners
Airport planner - 2: ground controller
Responsible for movements over the taxiways of the airport
Gives taxiing routes
Merges inbound and outbound traffic
Establishes departure sequences
Assesses runway and/or apron congestion to avoid taxiway congestion (use of holdings and parkings)
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Current airport planners
Airport planner - 3: tower controller
Responsible for traffic at runways
Usually one runway per tower controller
Segregated mode vs. mixed mode operations
Large aircraft separation necessary because of wake vortex and speed differences
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Current airport planners
Airport planner - 4: approach controller
Responsible for the airspace around the airport
Sequences arrival traffic
Uses STARs (Standard Arrival Routes) and stacks
Takes care of dependencies between runways (e.g. crossing runways or converging runways), always aware of overshoots or missed approaches
Determines the runway capacity
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Current airport planners
Airport planner - 5: supervisor
Responsible for the flow of traffic
Decides on runway usage
Assesses meteo and decides on airport acceptance rate (per hour) - information will be send to Brussels (CFMU)
Co-ordinates work of other controllers, assesses their workload and decides on division of work over 1 to 10 controllers
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Departure Management
How can AI Planning Help?
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Departure sequencing: model
SID way point
SID A start point
Runway 1holding
Runway2
Runway 2entry A
Runway 1entry A
Runway1
Runway 2holding
SID B start point
TMA exit point A
TMA exit point B
TaxiwaystructureApron
structure
Remaining SIDs
Remaining SIDs
Bottleneck
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Departure Sequencing Problem
Sequencing aircraft at the available runways
Computer assistance to the controller team in the control tower
Co-operate with other planners
Planning will be performed before the aircraft starts moving (20 - 30 minutes in advance). Tool provides sequences on an “optimal” basis, in stead of (smart) first-come-first-served
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What variables must be planned?
runway
SID
structure
2 min.
5 min.
exit
holding
A
* runway assignment
runway
holding
A2 min.
5 min.
exit
* intersection take-off* take-off time (sequences)* SID allocation
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NLR departure sequencer
The details of constraint reasoning
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What is planning
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
It takes into account the current situation, available resources, changing information, …
Many constraints
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Constraints
Some constraints are hard (CFMU, wake vortex, ..)
Some constraints are soft (distribution, pilot wishes, ..)
Constraints differ per airport
Constraints differ per “situation”
=> We need an implementation that follows all rules (regulations) but still provides some flexibility
=> AI Planning: constraint satisfaction with optimisation
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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]
C1 C2 C3 C4
C = [0, 1]
_ _________________
--
--
--
--
--
--
--C2 + S + M > 10
etc...
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Departure seq.: constraint satisfaction
Departure slots can be represented asF1runway = [16L, 16R, 34L, 34R, 07, 25]F1time = [4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19]F1SID = [ELBA5A, ELBA5B, ELBA5C]
F2runway = [16L, 16R, 34L, 34R, 07, 25]F2time = [4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19]F2SID = [ELBA5A, ELBA5B, ELBA5C]
Constraints: e.g. 3 min. separation between heavy - light:For F1 <> F2 and Runway (F1 = F2) and (Time(F1) < Time (F2)) and (Weight (F1) > Weight(F2))Conclude Time(F1) + 3 <= Time (F2)
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Departure Sequencing Problem
Runway assignment– Environmental constraints– Meteo conditions– Different runway entry points (CAVOK)
Separation– Wake vortex– Speed
Distribution– Initial climb routes/SIDs– TMA exit point acceptance rate
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Departure Sequencing Problem
Time– Achieve CFMU time constraints (flow restrictions)– Give preference to “late” aircraft
Optimisation– Minimise runway throughput– Make efficient use of available airspace– Depart as early as possible– Provide flexibility
Controller/pilot– Controller makes decisions, machine supports– Pilot may have preferences
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Departure sequencing: HMIs
-5 0 +5 +10 +15
+20
UTC
eobtetd
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
CSA978 N20 1910 1904 AT72/M LZKZ 24 RATIS 0336 J-H-B
FFR8105 N1 1920 1915 B733/M LDDU 24 BANAS2A 0232
CSA270 N9 1916 1909 B735/M HECA 24 RATIS 0331 NO PUSH
Active Departures
Delete Edit TWR/APP
-5 0 +5 +15+10
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Trial implementation at Prague airport (Integrated in the NOVA system)
-5 0 +5 +10 +15 +20
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Results so far and future work
-5 0 +5 +10 +15 +20
Where do we stand and what do we expect from the future
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Departure sequencing: concept
Departure sequence
Intersection take-off
Taxiway routing
Co-ordination
Apron management
Co-ordination
Start-up
Push back
De-icingRunway allocation
Wake vortex
Speed
Flow restrictions
CFMU slots
SID usage
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Controller support in planning
With the provision of a “ departure management” function, we will be able to:
Enable a better knowledge of the current and future situation (situation awareness)
Provide continuous optimal capacity
Provide the controller a new challenging operational task– make strategic decisions on departure management– provide advanced guidance– increase safety with new complex procedural demands
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Results so far Implementation in C++, connected to CORBA in A-SMGCS
simulator; core scheduler build in ILOG
Off-line DMAN evaluations at Rome-Fiumicino and Paris-Orly (1998-1999)
On-line DMAN tests at Prague and Hamburg (2001-2002)
Simulator trials for Frankfurt (2002)(Tower simulator)
Current activities:– Connection to pilot (CDM)– New trials with controllers in the simulator
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Results so far
In a new set up, we are investigating planning & negotiation algorithms: intelligent agents
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
Several papers have been published
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Planning and co-ordination
ActorAgent
Interface
Planner Agent
Planner Agent PlannerInterface
PlannerInterface
ActorAgent
Interface
Blackboard
Blackboardmanager
TARGET SETTING
ACTING
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Some results from operational trials
Prague evaluations (27 May - 7 June 2002)Hamburg evaluations (2 - 13 September 2002)
DMAN resulted in a smoother traffic flow for runway occupancy (results are obtained from simulator trials)
Training Session 2 Evaluation 1 (DMAN)Tower Controller no.2
0:00:00
0:01:26
0:02:53
0:04:19
0:05:46
1 2 3 4 5 6 7 8 9 10
Aircraft Number
Sepa
ratio
n Ti
me
(min
s an
d se
cs)
Training Session 2 Evaluation 2 (no DMAN)Tower Controller no.1
0:00:00
0:01:26
0:02:53
0:04:19
0:05:46
1 2 3 4 5 6 7 8 9 10
Aircraft Number
Sepa
ratio
n Ti
me
(min
s an
d se
cs)
DMAN No DMAN
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Future of airport planning
Planning is a novel concept to be supported
“Forces” controllers to evaluate start-up and push-back requests and gives additional information (situational awareness)
First efficiency benefit have been proven. New demands will arise for e.g. environmental monitoring, in which planning can provide great help
Changing operational procedures is not always appreciated; we slightly started to explore the possibility
Controller wants to be in command
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The result: