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Measurements of the quality of Traffic Orientation Schemes regarding flight plan efficiency
Markus Hantschke (TU Dresden – now with LH Systems)Urban Weisshaar (LH Systems)
Eighth USA/Europe Air Traffic Management Research and Development Seminar (ATM2009)Marcus Hantschke & Urban Weißhaar
30 Juni 2009 Chart 1
Agenda
Flight plan optimisation with Lido OC
Air Traffic Flow and Capacity Management (ATFCM) in Europe
Dynamic flight planning through consideration of Traffic Flow Restrictions
Measurement of the quality of the European Traffic Orientation Scheme (RAD)
Eighth USA/Europe Air Traffic Management Research and Development Seminar (ATM2009)Marcus Hantschke & Urban Weißhaar
30 Juni 2009 Chart 2
Focal point of flight dispatch activities is the flight path optimization
Optimization with respect to:
minimum timeminimum fuel carriedminimum cost
fuel costequipment costdelay and offload costcrew cost ...
... taking into account schedule constraints
Airline's Cost Philosophy
Analysis
OffloadCost
ATCCharges
FuelCost
CrewCost
AircraftCost
DelayCost
Eighth USA/Europe Air Traffic Management Research and Development Seminar (ATM2009)Marcus Hantschke & Urban Weißhaar
30 Juni 2009 Chart 3
Station-management
Manpower-Planning
FlightScheduling
PairingConstruct.
RosterGeneration
OperationsControl
CrewControl
CrewInformation
Mainten.Control
SlotRestrictions
AIP/NAVData
ScheduleData
OPSData
AircraftStatus
CommercialInfo
ATCCharges
FlightCrew
Notam
W&BData
Weather
LoadData
T/OPerformance
TrafficRights
FlowRestrictions
Lido OCInfluencing parameter to flight path optimization
Eighth USA/Europe Air Traffic Management Research and Development Seminar (ATM2009)Marcus Hantschke & Urban Weißhaar
30 Juni 2009 Chart 4
Departure Destination
Considered Segments during Optimisation
Eighth USA/Europe Air Traffic Management Research and Development Seminar (ATM2009)Marcus Hantschke & Urban Weißhaar
30 Juni 2009 Chart 5
Horizontal Optimisation
TO_WPT FROM_WPT CostABC
DEPDEPDEP
212523
AA
EB
5240
CG 45BB
EF
4953
GG
FJ
7379
EE
KH
8475
FF
HI
7067
II
LM
9685
HL 86JM 119KO 117KL 109MQ 115LP 118QDEST 134OP 136PDEST 130
WorklistDijekstra algorithm
DEP DEST
16
40
19
12
19J
28
34
I1417
O3325
Q30
P32F
2428
D
E
1931
G22
A
B
C
2125
23
H
K
35
26 L
M18
29
1.) Selection of segments for current from- waypoint
2.) Calculation of costs for selected segments
3.) Entering calculated datasets into worklist
4.) Selection of best dataset from worklist
5.) To- waypoint of best dataset becomes from- waypoint
Eighth USA/Europe Air Traffic Management Research and Development Seminar (ATM2009)Marcus Hantschke & Urban Weißhaar
30 Juni 2009 Chart 6
Departure DestinationWaypoint
FL350
FL310
FL280
FL260
FL240
FL220
Maximum flightlevel
Optimum flightlevel
Estimated T/O- weight
kgGWGW Landcalculated 20≤−
If
=> profile optimized!
Vertical Optimization
Eighth USA/Europe Air Traffic Management Research and Development Seminar (ATM2009)Marcus Hantschke & Urban Weißhaar
30 Juni 2009 Chart 7
Agenda
Flight plan optimisation with Lido OC
Air Traffic Flow and Capacity Management (ATFCM) in Europe
Dynamic flight planning through consideration of Traffic Flow Restrictions
Measurement of the quality of the European Traffic Orientation Scheme (RAD)
Eighth USA/Europe Air Traffic Management Research and Development Seminar (ATM2009)Marcus Hantschke & Urban Weißhaar
30 Juni 2009 Chart 8
Overview about Traffic Flow Management Procedures
Eighth USA/Europe Air Traffic Management Research and Development Seminar (ATM2009)Marcus Hantschke & Urban Weißhaar
30 Juni 2009 Chart 9
Basic principles of Traffic Flow Restrictions
Traffic Flow Restrictions organise a system of major traffic flows through congested areas.
Traffic Flow Restrictions are routeing requirements designed to make the most effective use of ATC capacity.
Traffic Flow Restrictions define restrictions on routes, through specified areas. Aircraft operators planning flights through these areas must flight/plan in accordance with these route restrictions.
Traffic Flow Restrictions may guarantee an optimum traffic flow.
Eighth USA/Europe Air Traffic Management Research and Development Seminar (ATM2009)Marcus Hantschke & Urban Weißhaar
30 Juni 2009 Chart 10
Basic principles of Traffic Flow Restrictions
Conditions like Departure / Destination / Via Waypoints including logical operators….
… inducing different types of dependencies (“and” / “or”) Careful interpretation needed
Eighth USA/Europe Air Traffic Management Research and Development Seminar (ATM2009)Marcus Hantschke & Urban Weißhaar
30 Juni 2009 Chart 11
Agenda
Flight plan optimisation with Lido OC
Air Traffic Flow and Capacity Management (ATFCM) in Europe
Dynamic flight planning through consideration of Traffic Flow Restrictions
Measurement of the quality of the European Traffic Orientation Scheme (RAD)
Eighth USA/Europe Air Traffic Management Research and Development Seminar (ATM2009)Marcus Hantschke & Urban Weißhaar
30 Juni 2009 Chart 12
Implementation of Traffic Flow Restrictions in Lido OC
TFR restriction : segment A – E ONLY AVAILABLE VIA waypoint O
Optimised & legal routing between Departure - Destination is determined during calculation.
Eighth USA/Europe Air Traffic Management Research and Development Seminar (ATM2009)Marcus Hantschke & Urban Weißhaar
30 Juni 2009 Chart 13
Agenda
Flight plan optimisation with Lido OC
Air Traffic Flow and Capacity Management (ATFCM) in Europe
Dynamic flight planning through consideration of Traffic Flow Restrictions
Measurement of the quality of the European Traffic Orientation Scheme (RAD)
Eighth USA/Europe Air Traffic Management Research and Development Seminar (ATM2009)Marcus Hantschke & Urban Weißhaar
30 Juni 2009 Chart 14
Methodology of Measuring the Quality of the RAD
Approach:Minimum Cost Tracks considering restrictions from the RAD (FPLTFR) are compared with Minimum
Cost Tracks not considering restrictions from the RAD (FPLnTFR)
the absolute or relative differences are calculated to indicate the absolute Cost Deviations (dabs) and the relative Cost Deviations (drel) for every flight event i (i= 1...n)
absolute Cost Deviation dabs i = di + TFR - di – TFR [USD]
relative Cost Deviation drel i = di + TFR / di – TFR [%]
The total deviation is calculated based on Cost Deviations from individual flight events
n
absolute Total Cost Deviation Dabs i = Σ dabs i / n [USD]i=1
n
relative Total Cost Deviation Drel i = Σ drel i / n [%]i=1
Eighth USA/Europe Air Traffic Management Research and Development Seminar (ATM2009)Marcus Hantschke & Urban Weißhaar
30 Juni 2009 Chart 15
Methodology of Measuring the Quality of the RAD
Weight factors (gi) can be used to consider importance of city pairs, airports, routes etc. Movements per year and Airport can be used as weight factor
nWeighted absolute Cost Deviation Dabs g= Σ (gi * di) [USD]
i=1
nWeighted relative Cost Deviation Drel g= Σ (gi * di) [%]
i=1
Eighth USA/Europe Air Traffic Management Research and Development Seminar (ATM2009)Marcus Hantschke & Urban Weißhaar
30 Juni 2009 Chart 16
Focus of Analysis / Sample Flights
Randomized sample of 90 European airports
11 Airports from this sample are used for deeper analysisParis Charles De Gaule (LFPG), Frankfurt Rhein/Main (EDDF), London Heathrow (EGLL), Amsterdam Schiphol
(EHAM), Madrid Barajas (LEMD), London Gatwick (EGKK), Brussel National (EBBR), Istanbul Atatürk Intl. (LTBA), Oslo Gardermoen (ENGM), Airport Köln/Bonn (EDDK) and Warsaw Okecie (EPWA)
Each of the 11 airports was used as central departure location to reach every other airport of the sample (“Departure-Star”) and additionally used as central destination from all other airports of the sample (“Destination-Star”)
Period of analysis 29th June to 28th July 2007
Settings of Lido environment:
Aircraft: Airbus A321-200; 75% Payload; 2h Holding FuelWeather: actual weather conditionsRegulations/ Restrictions: actual and all considered
Eighth USA/Europe Air Traffic Management Research and Development Seminar (ATM2009)Marcus Hantschke & Urban Weißhaar
30 Juni 2009 Chart 17
Sample of flights
Calculated routes of the sample*Example: Movements from and to Warsaw are colored in purple
Warsaw[EPWA]
Eighth USA/Europe Air Traffic Management Research and Development Seminar (ATM2009)Marcus Hantschke & Urban Weißhaar
30 Juni 2009 Chart 18
Results – Average Cost Deviations
Average Cost Deviation (not weighted) for the RAD*The following formula Relative Overall Cost Deviation was used
n
Drel i = Σ drel i / n [%]i=1
Drel i= 0,76%
Average Cost Deviation (weighted by movements per Airport) for the RAD*/**The following formula Weighted Relative Overall Cost Deviation was usedThe weight factors are based on annual movements on the respective airport in year2006
n
Drel g= Σ (gi * di) [%]i=1
DRAD= 0,83%* All routes of the sample considered** sample sorted by star-airport; weight factor based on movements 2006
Eighth USA/Europe Air Traffic Management Research and Development Seminar (ATM2009)Marcus Hantschke & Urban Weißhaar
30 Juni 2009 Chart 19
Individual Cost Deviations of “star-airports”
0,28
%
0,44
%
0,60
%
0,63
%
0,66
%
0,68
% 0,78
%
1,01
%
1,04
%
1,08
%
1,09
%
0,00%
0,20%
0,40%
0,60%
0,80%
1,00%
LTB
A
EN
GM
EG
KK
EG
LL
EP
WA
EH
AM
ED
DF
LEM
D
EB
BR
ED
DK
LFP
G
Airport
Cost
Dev
iatio
n
Cost Deviation
Measured Cost Deviations of airport stars (Dep/Dest)
Eighth USA/Europe Air Traffic Management Research and Development Seminar (ATM2009)Marcus Hantschke & Urban Weißhaar
30 Juni 2009 Chart 20
Cost Deviation related to route length*
* All routes of the sample considered** Longest route in the sample Oslo – Pafor (1879NM)
0,21
%
0,90
%
0,93
%
0,98
%
0,58
% 0,65
%
0,59
%
0,58
%
0,58
%
0,58
%
0,42
%
0,37
%
0,20
%
0,00%
0,10%
0,20%
0,30%
0,40%
0,50%
0,60%
0,70%
0,80%
0,90%
1,00%
(0-15
0](15
0-300
](30
0-450
](45
0-600
](60
0-750
](75
0-900
](90
0-105
0](10
50-12
00]
(1200
-1350
](13
50-15
00]
(1500
-1650
](16
50-18
00]
and h
igher
Class of Distance
Cos
t Dev
iatio
n
0-150NM: Only 13% of routes have Cost
Deviation >0,00%Main case: SID touches STAR
150-600NM:35% of Cost Deviation caused by
FL limitations (CPLC)600NM-1500NM:
Cost Deviation only effected by route restrictions
>1500NM:Cost deviation is decreasing
continually down to 0,20%**
Cost Deviation depending on route length
Eighth USA/Europe Air Traffic Management Research and Development Seminar (ATM2009)Marcus Hantschke & Urban Weißhaar
30 Juni 2009 Chart 21
Average route distances for all star-airports
Location of analyzed airports causes different average route distancesThis influence to be removed to compare the quality of the RAD inside the group of analyzed airports
Average route length of analyzed routes for every airport star
1099
890
870
764
721
598
592
591
582
569
563
0
200
400
600
800
1000
EGKK EBBR EDDK LFPG EDDF EHAM EGLL EPWA ENGM LEMD LTBA
Airport [ICAO]
Rou
te D
ista
nce
[NM
]
Eighth USA/Europe Air Traffic Management Research and Development Seminar (ATM2009)Marcus Hantschke & Urban Weißhaar
30 Juni 2009 Chart 22
Specific Cost Deviations of analyzed star-airports
1,04
%
1,08
%
1,09
%
0,78
%
0,68
%
0,60
%
0,63
%
0,66
%
0,44
%
1,01
%
0,28
%
0,98
%
0,98
%
0,98
%
0,98
%
0,98
%
0,98
%
0,58
% 0,65
%
0,65
%
0,65
%
0,58
%
0,00%
0,20%
0,40%
0,60%
0,80%
1,00%
EBBR EDDK LFPG EDDF EHAM EGKK EGLL EPWA ENGM LEMD LTBA
Airport
Cost
Dev
iatio
n
total dependend on route distance
Average Cost Deviations for Analysed Airports*
* Data should be used for further analysis
Eighth USA/Europe Air Traffic Management Research and Development Seminar (ATM2009)Marcus Hantschke & Urban Weißhaar
30 Juni 2009 Chart 23
Differences of specific Cost Deviations of analyzed Airports
-0,10% -0,11%
0,20%
0,30%
-0,01%
0,21%
0,30%
-0,06%
0,38%
-0,05%
-0,36%-0,50%
-0,40%
-0,30%
-0,20%
-0,10%
0,00%
0,10%
0,20%
0,30%
0,40%
0,50%
EBBR EDDK LFPG EDDF EHAM EGKK EGLL EPWA ENGM LEMD LTBA
Airport [ICAO]
Diff
eren
ce o
f Cos
t Dev
iatio
ns [%
]
Differences between Distance Based Cost Deviation and Measured Cost Deviation for Analysed Airports*
*Data should be used for further analysis
Eighth USA/Europe Air Traffic Management Research and Development Seminar (ATM2009)Marcus Hantschke & Urban Weißhaar
30 Juni 2009 Chart 24
Additional effort caused by the RAD in absolute values*
24 27 24 18 9 6 9 6 4 1 1 1 7
608
478
211
128
105
84 65 560
100
200
300
400
500
600
(0-2
5]
(25-
50]
(50-
75]
(75-
100]
(100
-125
]
(125
-150
]
(150
-175
]
(175
-200
]
(200
-225
]
(225
-250
]
(250
-275
]
(275
-300
]
(300
-325
]
(325
-350
]
(350
-375
]
(375
-400
]
(400
-425
]
(425
-450
]
(450
-475
]
(475
-500
]
and
high
erClass of Additional Fuel [kg]
Freq
uenc
y
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Dis
trib
utio
n
Frequency Distribution
* Results depend on the used aircraft type and the boundary conditions of this analysis
754412276295
183
494
1016
0
200
400
600
800
1000
(0-1
0]
(10-
20]
(20-
30]
(30-
40]
(40-
50]
(50-
60]
(60-
70]
(70-
80]
(80-
90]
(90-
100]
and
high
er
Class of Distances [NM]
Freq
uenc
y
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Dis
trib
utio
n
Frequency Distribution
60% of cases: additional fuel <25kg95% of cases: additional fuel <225kg(not enough for 5min flight)
50% of cases: additional distance <10NM80% of cases: <20NM95% of cases: <50NM
Distribution and Frequency of Additional Trip Fuel Distribution and Frequency of Route Extension
Eighth USA/Europe Air Traffic Management Research and Development Seminar (ATM2009)Marcus Hantschke & Urban Weißhaar
30 Juni 2009 Chart 25
Contacts
Marcus HantschkeSystem Engineer
Lufthansa Systems Aeronautics GmbHFRA OD/I-FAm Prime Parc 265479 Raunheim
Tel: +49 (0)69 696 56763Fax: +49 (0)69 696 90077
E-Mail: marcus.hantschke@lhsystems.com
Urban WeißhaarTeamleader Product Development
Lufthansa Systems Aeronautics GmbHFRA OD/DAm Prime Parc 265479 RaunheimGermany
Tel. +49 (0) 69 696 93994Mobil: +49 (151) 58920063Fax +49 (0) 69 696 90077
E-Mail: Urban.Weisshaar@lhsystems.com
Thank you for your attention!
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