D A I-II - ITU AVIATION INSTITUTE Main Pageaviation.itu.edu.tr/img/aviation/datafiles/Lecture...

DATA ANALYTICS IN AIR TRANSPORTATION SYSTEMS I-II

DR EMRE KOYUNCU (ISTANBUL TECHNICAL UNIVERSITY)

Advanced Information Systems

Module 5-9 1-6 June 2015

Istanbul Technical University

Air Transportation Management

MSc Program

LEARNING OBJECTIVES

bull Data Analytics in AT

ndash TBO Flight Operation case

ndash Flight Incidents case

ndash FDM based flight performance analysis

ndash Delay Propagation in ATM Network

TRAJECTORY BASED-OPERATIONS (TBO)

bull A New ATM Paradigm Trajectory Based-Operations (TBO)

- Key feature of the target concept of operations proposed by SESAR and NextGen

- Collaborative management of business trajectories supported by advanced trajectory-based

automation tools

- Trajectory-based automation tools rely on trajectory prediction

- To support the interoperability between disparate trajectory-based automation tools

there is a need for mechanisms to synchronise Trajectory Predictors (TPs)

- TP synchronisation is a key prerequisite for the SESARNext Gen concepts

- The REACT project has focused on one of the types of information that can be

shared between TPs to achieve synchronisation the Aircraft Intent

A BIT OF TERMINOLOGY

bull Business Trajectory

ndash Represents the businessmission intention of an airspace user

ndash Evolves through a collaborative planning process that involves users and ATM service providers and whose outcome should be a trajectory that results in minimum deviations from the user preferences

bull Interoperability is a property referring to the ability of diverse systems to work together (inter-operate)

bull A key necessary condition for the interoperability of trajectory-based automation tools is the synchronisation of the underlying TPs

bull The synchronisation of two TPs results in a minimally acceptable difference between the trajectory outputs of those TPs (this minimally acceptable difference depends on the applications supported by the TPs)

5

TOWARDS TRAJECTORY BASED OPERATIONS (TBO)

City B

AOC1

AOC2

ANSP1

ANSP2

ANSP3

ANSP4

ANSP1

BUSINESS TRAJECTORIES

ANSP= Air Navigation Service Provider

AOC= Airline Operations Centre

6

TOWARDS TBO INTEROPERABILITY AND TP SYNCHRONISATION

TRAJECTORY RELATED

INFORMATION

AOC1

AOC2

ANSP1

ANSP2

ANSP3

ANSP1

ANSP4

7

TRAJECTORY RELATED

INFORMATION


TP2

TPI

TP1

TPP

TP6

TPN

TP3

TPR

TP4

TPK

TP5

TPL

TPH

CDampR

ASAS

FMS

AMANFDPS

FMS

FMS

ATFM

AMAN= Arrival manager

DMAN= Departure manager

FMS= Flight Management System

FP=Flight Planning

ASAS=Airborne Separation Assurance System

ATFM=Air Traffic Flow Management

FDPS=Flight Data Processing Tool

CDampR=Conflict Detection and Resolution

Actual aircraft state

(position speed

weighthellip)

MORE TERMINOLOGY TRAJECTORY-RELATED INFORMATION

Environmental

Conditions

Pilot

Real World

Trajectory Prediction (Air or Ground)

Flight Commands

amp Guidance

Modes

Flight

Intent

Flight

Plan

Tactical

Amendments to

Flight Plan

Airborne

Automation

System

Actual

Trajectory

Aircraft

Predicted

Trajectory

Trajectory

Computation

Infrastructure

Aircraft

Intent

Intent

Generation

Infrastructure

Initial

Conditions

Trajectory Predictor (TP)

AT or ABOVE FL290

SHARING TRAJECTORY-RELATED INFORMATION

Data COM InfrastructurePredicted trajectory

information

Flight

Intent

Airborne

Predicted

Trajectory

TP PROCESS 2 (eg arrival manager)

Flight

Intent

Ground

Predicted

Trajectory

Trajectory

Computation

Infrastructure

(1)

Aircraft

Intent

Intent

Generation

Infrastructure

(1)

Airborne TP

Trajectory

Computation

Infrastructure

(2)

Aircraft

Intent

Intent

Generation

Infrastructure

(2)

Ground TP

Aircraft Intent

information

Flight Intent

Information

Trajectory Prediction (eg flight management system)

bull Two levels in the language grammar lexical and syntactical

bull Lexical Level Instructions

ndash Instructions are atomic inputs to the Trajectory Engine that capture basic

commands and guidance modes at the disposal of the pilotFMS to direct the

operation of the aircraft

bull Syntactical level Operations

ndash Operations are sets of compatible instructions that when simultaneously active

univocally determine the ensuing aircraft motion

bull With a reduced set of instructions (AIDL alphabet) any possible aircraft

operation can be formally specified in such a way that the ensuing aircraft

motion is unambiguously determined


11

Next generation

FMS

AOC 2

ATFM DST

FMS

AOC 1

FDPS

AMAN DST

Next

Generation

FDPS

Air-Air

Air-Ground

Ground-Ground


12

TRAJECTORY RELATED INFORMATION

AIRCRAFT INTENT

TP2

TPI

TPP

TPR

TPK

TP5

TPL

TPH

Translator

I-5

Translator

R-5

Translator

2-K

Translator

R-2

Translator

2-5

Translator

I-2

Translator

H-5

Translator

R-P

N (N-1) divide 2TRANSLATORS

Translator

K-P

Translator

5-K

Translator

I-R

Translator

5-P

Translator

L-5

Translator

I-H

Translator

H-L

Translator

R-K

Translator

L-P


13

TP2

TPI

TPP

TPR

TPK

TP5

TPL

TPH

Translator

L-AIDL

AIDL

Translator

5-AIDL

Translator

P-AIDL

Translator

K-AIDL

Translator

R-AIDL

Translator

2-AIDL

Translator

H-AIDL

Translator

I-AIDL

N TRANSLATORS


externalinternal

Constraints amp

Rules

Aeronautical

Nav Data

Weather

Data

Basic Flight

Data amp

Schedule

Route Type amp

Optimization

Settings

Aircraft

Performance

Data

Business Rules

euroFlight

Number

City Pair

Alternate

ADES

DOF STD

Fuel Policy AC Type

AC

Equipment

AC

Envelope

Payload

Payload -

Range

Wind

Condition

Air Pressure

Air Temp

Natural

Hazards

Stat Dyn

Routes

Fix Free

Route

Opt Criteria

Cost Index

Traffic

Rights

RNAV Rules

NOTAM

TFR

(eg RAD)

Terrain

Clearance

Terminal

Procedures

DCT

Connection

Airport

Definition

Flight

connectivity

Human Req

Time Costs

Business

Targets

Business

Constraints

Conditional

Routes

DATA TYPES

bull METARTAF

LTBA 312020Z 05006KT 030V100 CAVOK 1908 Q1018 NOSIG

TAF LTBA 311640Z 31180124 03009KT CAVOK

BECMG 01030106 SCT035

TEMPO 01080112 04015G25KT

BECMG 01140116 CAVOK

Weather

Data

METAR EXPLAINED

KTTN 051853Z 04011KT 12SM VCTS SN FZFG BKN003 OVC010 M02M02 A3006 RMK AO2 TSB40

SLP176 P0002 T10171017

bull KTTN is the ICAO identifier for the Trenton-Mercer Airport

bull 051853Z indicates the day of the month is the 5th and the time of day is 1853 ZuluUTC 653PM GMT

or 153PM Eastern Standard Time

bull 04011KT indicates the wind is from 040deg true (north east) at 11 knots (20 kmh 13 mph) In the United

States the wind direction must have a 60deg or greater variance for variable wind direction to be reported

and the wind speed must be greater than 3 knots (56 kmh 35 mph)

bull 12SM indicates the prevailing visibility is 1frasl2 mi (800 m) SM = statute mile

bull VCTS indicates a thunderstorm (TS) in the vicinity (VC) which means from 5ndash10 mi (8ndash16 km)

bull SN indicates snow is falling at a moderate intensity a preceding plus or minus sign (+-) indicates heavy

or light precipitation Without a +- sign moderate precipitation is assumed

bull FZFG indicates the presence of freezing fog

bull BKN003 OVC010 indicates a broken (58 to 78 of the sky covered) cloud layer at 300 ft (91 m) above

ground level (AGL) and an overcast (88 of the sky covered) layer at 1000 ft (300 m)

bull M02M02 indicates the temperature is minus2degC (28degF) and the dewpoint is minus2degC (28degF) An M in

front of the number indicates that the temperaturedew point is minus ie below zero (0) Celsius

bull A3006 indicates the altimeter setting is 3006 inHg (1018 hPa)

bull RMK indicates the remarks section follows

DATA TYPES

bull Aeronautical Information Manual (AIM)

ndash SID and STAR Taxi charts

Aeronautical

Nav Data

SID

STAR

DATA TYPES

bull Airspace rules

ndash Eg seperation

Constraints amp

Rules

DATA TYPES

bull Cost Index

bull Airline (User) preferred routes

ndash User Preferences Model (UPM)

Route Type amp

Optimization

Settings

COST DEFINITION

COST INDEX EXAMPLE

TRAJECTORY PREDICTION ENGINE

FIDL EXAMPLE

INPUTS

bull Initial conditions (IC)

bull Flight Intent (FI)

bull User Preferences Model (UPM)

ndash ie airline policy

bull Operational Context Model (OCM)

ndash rules of airpace including

STARs and SIDs

bull ie ATFM policy

ndash Aircraft Performance Model

(APM)

bull Based on BADA

ndash Weather Model (WM)


FIDL EXAMPLE

bull Flight Intent with User Preferences Model (UPM)


FIDL EXAMPLE

bull FI with UPM and Operational Context Model (OCM)


FIDL EXAMPLE

bull Output 4D trajectory


FIDL EXAMPLE

bull Output 4D trajectory with details

DATA TYPES

bull Flight Plan

bull Regulated Flight Plan

bull Actual Flight data (Current Tactical)

bull Correlated Position data

bull CDM related data

Basic Flight

Data amp

Schedule

4D TRAJECTORY DATA PROFILES

LIPEEDFMJMP803JMPD22820110301031200BB9377945220110301031500FPLFPLAFPNEXENEXENNN2011030103150020110301031500TEFINS783849NNN00ACHN

NNN600300N00N0NDCULTNRSNNK00344154791F160N0234019032500LIPELUPOS5N10A443151N0111749EY

032955DCT7518V443121N0110416E32Y 033515DCT15038V443048N0104912E67Y 033640DCT16043V443040N0104526E75Y

033830LUPOSL99516057W443017N0103453EY 034355PARL99516099N444920N0101736EY 034735MISPOL995160127W450126N0100450EY

035305BEKANL995160169W451930N0094540EY 035720TZOL995160202N453333N0093026EY 040450PEPAGN851160260W455902N0090417EY

040730ABESIN851160280W460935N0090234EY 041350PIXOSN851160329W463619N0085859EY 041800SOPERN851160361W465322N0085640EY

042155ELMURN851160391W470924N0085427EY 042350ROLSAN851160406W471723N0085321EY 042705KUDESDCT160431W473115N0085126EN

044840DCT160597V490001N0083550E76N 045435DCT75623V491355N0083323E88N

050205EDFM3650A492821N0083051EN23032500LI040545NAS443151N0111749E460244N0090341E11600267

032500LIMMFIR040545FIR443151N0111749E460244N0090341E11600267 032500LIPECR033115ES443151N0111749E443113N0110030E194023

032500LIPECTR033115AUA443151N0111749E443113N0110030E194023 033115LIPPADS033735ES443113N0110030E443029N0104009E941602350

033115LIPPC1X033735ES443113N0110030E443029N0104009E941602350 033115LIPPCTA033735AUA443113N0110030E443029N0104009E941602350

033735LIMMECTA034805AUA443029N0104009E450310N0100300E16016050131 033735LIMMES1034805ES443029N0104009E450310N0100300E16016050131

033735LIMMES1X034805ES443029N0104009E450310N0100300E16016050131 034635LIMMR60041420ES445759N0100829E463827N0085842E160160119333

034805LIMMACTA040730AUA450310N0100300E460935N0090234E160160131280 034805LIMMADE035640ES450310N0100300E453126N0093244E160160131197

035640LIMMANE040730ES453126N0093244E460935N0090234E160160197280 040545LS042705NAS460244N0090341E473115N0085126E160160267431

040545LSASFIR042705FIR460244N0090341E473115N0085126E160160267431 040730LSAZCTA042705AUA460935N0090234E473115N0085126E160160280431

040730LSAZSSL042420ES460935N0090234E471936N0085303E160160280410 041545LSTSA50P042020CRSA464419N0085754E470300N0085520E160160344379

041545LSTSA52P041620ERSA464419N0085754E464627N0085736E160160344348 041620LSTSA51P042020ERSA464627N0085736E470300N0085520E160160348379

042020LSTSA40P042115ERSA470300N0085520E470644N0085449E160160379386

042420LSAZESL042705ES471936N0085303E473115N0085126E1601604104310344157065F160N02340 F140N023493 F160N023498 F150N0234390

F100N023439778032200LIPELUPOS5N10A443151N0111749EY 032540DCT6014V443128N0110716E25Y 032730DCT6022V443115N0110115E39Y

032800DCT6824V443111N0105944E42Y 032830DCT7027V443106N0105729E47Y 032845DCT7528V443105N0105644E49Y 032855DCT7829V443103N0105558E51Y



033155DCT11045V443037N0104355E79Y 033215LUPOSL99511057W443017N0103453EY 033240DCT11071V443638N0102907E33Y




033700DCT14094V444704N0101939E88Y 033740DCT14098V444853N0101801E98Y 033755PARL99514499N444920N0101736EY

034015DCT144120V445825N0100802E75Y 034110MISPOL995145127W450126N0100450EY 034200DCT145134V450427N0100138E17Y



034625DCT160162V451629N0094852E83Y 034720BEKANL995160169W451930N0094540EY 035145TZOL995160202N453333N0093026EY

035700DCT160242V455107N0091224E69Y 035925PEPAGN851160260W455902N0090417EY 040205ABESIN851160280W460935N0090234EY

040715DCT160319V463052N0085943E80Y 040840PIXOSN851160329W463619N0085859EY 041315SOPERN851160361W465322N0085640EY

041720DCT160390V470852N0085431E97Y 041730ELMURN851157391W470924N0085427EY 041755DCT150393V471028N0085418E13Y

041820DCT150397V471236N0085401E40Y 041920DCT150405V471651N0085325E93Y 041935ROLSAN851147406W471723N0085321EY


042225DCT134427V472902N0085144E84Y 042240DCT130428V472935N0085140E88Y 042320KUDESN851121431W473115N0085126EN

042435DCT100437V473343N0085439E21N 042720ROMIRN851100459W474247N0090628EN 042825VEDOKN851100468W474724N0090714EN

042905TINOXDCT100473W475007N0090740EY 044335DCT100571G484048N0084511EY 045005DCT100607V485957N0083916E68Y


045240DCT74619V490620N0083717E91Y 045345INKAMDCT54624W490900N0083628EY 045655DCT54642V491820N0083258E56Y

045950DCT16656G492536N0083015EY 050110EDFM3661A492821N0083051EY39032200LI040020NAS443151N0111749E460244N0090341E11600267






Tactical flight Models

bull FTFM - Filed Tactical Flight Model The FTFM is the

ldquoinitialrdquo profile as it reflects the status of the demand before

activation of the regulation plan It is computed with the latest

flight plan version sent by each AO to the CFMUIFPS

bull RTFM - Regulated Tactical Flight Model The RTFM is the

ldquoregulatedrdquo profile as it reflects the status of the demand after


ATFM slot (CTOT) issued to the AO by the ground

regulation system

bull CTFM - Current Tactical Flight Model The CTFM is the

ldquoactualrdquo profile as it integrates the actual entry time of the

flights in the regulated TV It is computed with the Radar

Data sent by ACCs to CFMUETFMS ref

CPG_GEN - Profiles generated by the CFMU path generation

tool

bull SCR - Shortest Constrained Route

bull SRR - Shortest RAD restriction applied Route

bull SUR - Shortest Unconstrained Route

bull DCT - Direct route

CPF - Correlated Position reports for a Flight CPRs

(Correlated Position Reports) which are surveillance data

collected from the ACCs

Filed Flight Plan

CDM

Header

Point Profile

Airspace Profile

Circle Intersection

Profile

RTFM Profile

CTFM Profile

CFP Profile

FTFM Profile


Current Tactical Flight Model (CTFM) is computed with Radar Data sent by

Area Control Centers to CFMUETFMS so it can be deemed as a fused

version of FTFM with real data

ENHANCED TACTICAL FLOW MANAGEMENT SYSTEM (ETFMS) EUROCONTROL 2013

DATA TYPES

bull Base of Aircraft Data (BADA) depending on ac type

ndash Nominal control variables (BADA 3)

ndash Full flight variable envelope (BADA 4)

bull optimization

Aircraft

Performance

Data

AIRCRAFT EQUATION OF MOTION

bull equation of motion sufficient in 3 dof

High-lift device

landing gear and speed brakes

Local pressure ratio temp ratio

acc of gravity and wind speed vector

number of parameters of the system that may vary independently

BASE OF AIRCRAFT DATA (BADA)

bull There are two families of BADA APM based on the same modelling approach and components [EUROCONTROL]

bull BADA Family 3ndash providing a 90 coverage of the current aircraft types operating

in the ECAC airspace

ndash model aircraft behaviour over the normal operations part of the flight envelope and to meet todays requirements for aircraft performance modelling and simulation

bull BADA Family 4 ndash a newly developed model intended to meet advanced functional

and precision requirements of the new ATM systems

ndash providing a 60 coverage of the current aircraft types operating in ECAC airspace

ndash BADA 4 provides accurate modelling of aircraft over the entire flight envelope and enables modelling and simulation of advanced concepts of future systems

AIRCRAFT PERFORMANCE MODEL

High-lift device




BADA AIRCRAFT LIMITATION MODEL

DATA TYPES

bull Business objectives

ndash Cost Index


ndash Ground delays due to connectionshellip

Business Rules

euro

HORIZONTAL OPTIMISATION

TO_WPT FROM_WPT Cost

A

B

C

DEP

DEP

DEP

21

25

23

A

A

E

B

52

40

CG 45

B

B

E

F

49

53

G

G

F

J

73

79

E

E

K

H

84

75

F

F

H

I

70

67

I

I

L

M

96

85

HL 86

JM 119

KO 117

KL 109

MQ 115

LP 118

QDEST 134

OP 136

PDEST 130

Worklist

Dijkstra algorithm

DEPDEST

16

40

19

12

19

J

28

34

I14

17

O33

25

Q30

P32

F24

28

D

E

19

31

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

Departure DestinationWaypoint

FL350

FL310

FL280

FL260

FL240

FL220

Maximum flightlevel

Optimum flightlevel

Estimated TO- weight

kgGWGW Landcalculated 20

If

=gt profile optimized

DIJKSTRAS ALGORITHM

Dijkstras algorithm - is a solution to the single-source shortest path problem in graph theory

Works on both directed and undirected graphs However all edges must have nonnegative weights

Approach Greedy

Input Weighted graph G=EV and source vertex visinV such that all edge weights are nonnegative

Output Lengths of shortest paths (or the shortest paths themselves) from a given source vertex visinV to all other vertices

DIJKSTRAS ALGORITHM - PSEUDOCODE

dist[s] larr0 (distance to source vertex is zero)for all v isin Vndashs

do dist[v] larrinfin (set all other distances to infinity) Slarrempty (S the set of visited vertices is initially empty) QlarrV (Q the queue initially contains all vertices) while Q neempty (while the queue is not empty) do u larr mindistance(Qdist) (select the element of Q with the min distance)

SlarrScupu (add u to list of visited vertices) for all v isin neighbors[u]

do if dist[v] gt dist[u] + w(u v) (if new shortest path found)then d[v] larrd[u] + w(u v) (set new value of shortest path)

(if desired add traceback code)return dist

DIJKSTRA ANIMATED EXAMPLE










bull To understand how it works wersquoll go over the previous example again However we need two mathematical results first

bull Lemma 1 Triangle inequalityIf δ(uv) is the shortest path length between u and vδ(uv) le δ(ux) + δ(xv)

bull Lemma 2 The subpath of any shortest path is itself a shortest path

bull The key is to understand why we can claim that anytime we put a new vertex in S we can say that we already know the shortest path to it

bull Now back to the examplehellip

DIJKSTRAS ALGORITHM - WHY IT WORKS

APPLICATIONS OF DIJKSTRAS ALGORITHM

- Traffic Information Systems are most prominent use- Mapping (Map Quest Google Maps) - Routing Systems

SID

Solutions for a calculation of real flown

SIDs and STARs

The system should determines

Actual used RWY according the

Wind forecast

Take the shortest SID and STAR

into consideration during the

calculation

Optimize the entire route from

runway to runway

STAR

CONSIDERATION OF ESCAPE AIRPORTS

EN-ROUTE TERRAIN ANALYSIS

Enroute alternate 1

Enroute alternate 3

Escape route

Flight direction

Terrain

Continuing point

No-Return point

Diversion area

Area where direct segments

are sufficient to ensure terrain

clearance to enroute alternate

Decision points

Area where escape route

is (partially) required to

ensure terrain clearance

Enroute alternate 2

The Traffic Flow Restriction problem

The least cost path problem in connection

with TFR rules is an so called

NP-complete problem

the most notable characteristic of NP-

complete problems is that no fast solution to

them is known That is the time required to

solve the problem using any currently known

algorithm increases very quickly as the size

of the problem grows

4D TRAJECTORY + TIME BASED FLOW MANAGEMENT

Defined lateralvertical dimensions

+ time allocation

V

L

T

AIRSPACE DEMAND DATA ndash FLEXIBLE USE OF AIRSPACE

Trajectory Planning with and without airspace demand data load indications

Depending on the load in a defined sector the AU may avoid it or accept a delay

The sectors could be pre-defined (eg functional airspace blocks) or defined by NM

individually on ad hoc basic per each individual flight

The picture is only to demonstrate a general idea and not a final approved concept

OVERALL ATCFM OPTIMISITION BIG DATA

HOW BIG DATA MINING

MIGHT COMPLEMENT TODAYrsquoS APPROACHES

Todayrsquos solution approaches

Massive parallel computing

New Algorithm design From Dijkstra to

Ant-Colony

Branch amp Bound

Bidirectional Search

Evolution Strategy

Dynamic Programming

Simulated Annealing

Tabu-Search

Particle Swarm

HOW TO USE BIG DATA

Single Flight Event optimization has to be extended to

interdependent multidimensional air traffic system

optimization

Complex and high dynamic data pattern of traffic

schema need to be processes in shortest time intervals

Supercomputer might be essential to process the

gigantic amount of changing data to support ATC to de-

conflict traffic and optimize at the same time flight

efficiency

Lower Airspace

Manual ATC de-conflicting need big data support

OVERALL ATCFM OPTIMISATION BIG DATA

How could classical optimisation procedures be combined with big data technologies

TRAJECTORY GENERATION WITHIN DIFFERENT SYSTEMS

AIRLINE OPS CENTRE VS NETWORK MANAGER AIR TRAFFIC CONTROL SYSTEMS

euro

AOC

calculate 4D trajectories

with small volume accuracy

spaces

intention is optimized in best

way through the AOC

accuracy space

NM ATC

calculate 4D trajectories but

the accuracy spaces will be

wide

make assumptions to overcome

the gaps within the input

parameters

accuracy space

SESARrsquos Business Trajectory

SESARrsquoS BUSINESS TRAJECTORY

DIFFERENT REQUIREMENTS ON

BUSINESS TRAJECTORIES PER STAKEHOLDER

Needs

New technologies supporting de-conflicting on a totally different level

Automation to a maximum level

4D trajectories providing maximum flight efficiency from single flight event to the overall system efficiency

Airspace

User

ATC(Cost efficient)

NM Flow management and conflict resolution

providing maximum flight efficiency and ATM capacity

Use of Big data Optimisation with Big Data

BIG DATA IN COMBINATION WITH

CLASSICAL OPTIMISATION TECHNOLOGIES

INCIDENT ANALYSIS

INCIDENT ANALYSIS

PREDICTIVE INCIDENT ANALYSIS

72



CAUSE-CONSEQUENCE CHAINS

ASKING RIGHT QUESTION

PARAMETER ESTIMATION

77

PROOF OF MODEL

78

QUANTIFYING MAIN DRIVERS

79

CHANGE MANAGEMENT

80

IDENTIFYING UNKNOWNS

GAP ANALYSIS

82


LEARNING OBJECTIVES

bull Data Analytics in AT

ndash TBO Flight Operation case

ndash Flight Incidents case

ndash FDM based flight performance analysis

ndash Delay Propagation in ATM Network





automation tools














5


City B

AOC1

AOC2

ANSP1

ANSP2

ANSP3

ANSP4

ANSP1




6


TRAJECTORY RELATED

INFORMATION

AOC1

AOC2

ANSP1

ANSP2

ANSP3

ANSP1

ANSP4

7

TRAJECTORY RELATED

INFORMATION


TP2

TPI

TP1

TPP

TP6

TPN

TP3

TPR

TP4

TPK

TP5

TPL

TPH

CDampR

ASAS

FMS

AMANFDPS

FMS

FMS

ATFM




FP=Flight Planning






(position speed

weighthellip)


Environmental

Conditions

Pilot

Real World


Flight Commands

amp Guidance

Modes

Flight

Intent

Flight

Plan

Tactical

Amendments to

Flight Plan

Airborne

Automation

System

Actual

Trajectory

Aircraft

Predicted

Trajectory

Trajectory

Computation

Infrastructure

Aircraft

Intent

Intent

Generation

Infrastructure

Initial

Conditions


AT or ABOVE FL290



information

Flight

Intent

Airborne

Predicted

Trajectory


Flight

Intent

Ground

Predicted

Trajectory

Trajectory

Computation

Infrastructure

(1)

Aircraft

Intent

Intent

Generation

Infrastructure

(1)

Airborne TP

Trajectory

Computation

Infrastructure

(2)

Aircraft

Intent

Intent

Generation

Infrastructure

(2)

Ground TP

Aircraft Intent

information

Flight Intent

Information














11

Next generation

FMS

AOC 2

ATFM DST

FMS

AOC 1

FDPS

AMAN DST

Next

Generation

FDPS

Air-Air

Air-Ground

Ground-Ground


12


AIRCRAFT INTENT

TP2

TPI

TPP

TPR

TPK

TP5

TPL

TPH

Translator

I-5

Translator

R-5

Translator

2-K

Translator

R-2

Translator

2-5

Translator

I-2

Translator

H-5

Translator

R-P


Translator

K-P

Translator

5-K

Translator

I-R

Translator

5-P

Translator

L-5

Translator

I-H

Translator

H-L

Translator

R-K

Translator

L-P


13

TP2

TPI

TPP

TPR

TPK

TP5

TPL

TPH

Translator

L-AIDL

AIDL

Translator

5-AIDL

Translator

P-AIDL

Translator

K-AIDL

Translator

R-AIDL

Translator

2-AIDL

Translator

H-AIDL

Translator

I-AIDL

N TRANSLATORS


externalinternal

Constraints amp

Rules

Aeronautical

Nav Data

Weather

Data

Basic Flight

Data amp

Schedule

Route Type amp

Optimization

Settings

Aircraft

Performance

Data

Business Rules

euroFlight

Number

City Pair

Alternate

ADES

DOF STD

Fuel Policy AC Type

AC

Equipment

AC

Envelope

Payload

Payload -

Range

Wind

Condition

Air Pressure

Air Temp

Natural

Hazards

Stat Dyn

Routes

Fix Free

Route

Opt Criteria

Cost Index

Traffic

Rights

RNAV Rules

NOTAM

TFR

(eg RAD)

Terrain

Clearance

Terminal

Procedures

DCT

Connection

Airport

Definition

Flight

connectivity

Human Req

Time Costs

Business

Targets

Business

Constraints

Conditional

Routes

DATA TYPES

bull METARTAF



BECMG 01030106 SCT035

TEMPO 01080112 04015G25KT


Weather

Data

METAR EXPLAINED


SLP176 P0002 T10171017


















DATA TYPES



Aeronautical

Nav Data

SID

STAR

DATA TYPES

bull Airspace rules

ndash Eg seperation

Constraints amp

Rules

DATA TYPES

bull Cost Index



Route Type amp

Optimization

Settings

COST DEFINITION

COST INDEX EXAMPLE


FIDL EXAMPLE

INPUTS







STARs and SIDs

bull ie ATFM policy


(APM)

bull Based on BADA



FIDL EXAMPLE



FIDL EXAMPLE



FIDL EXAMPLE



FIDL EXAMPLE


DATA TYPES

bull Flight Plan





Basic Flight

Data amp

Schedule









044840DCT160597V490001N0083550E76N 045435DCT75623V491355N0083323E88N












042020LSTSA40P042115ERSA470300N0085520E470644N0085449E160160379386








































regulation system






tool








Filed Flight Plan

CDM

Header

Point Profile

Airspace Profile

Circle Intersection

Profile

RTFM Profile

CTFM Profile

CFP Profile

FTFM Profile






DATA TYPES




bull optimization

Aircraft

Performance

Data



High-lift device















High-lift device





DATA TYPES


ndash Cost Index



Business Rules

euro



A

B

C

DEP

DEP

DEP

21

25

23

A

A

E

B

52

40

CG 45

B

B

E

F

49

53

G

G

F

J

73

79

E

E

K

H

84

75

F

F

H

I

70

67

I

I

L

M

96

85

HL 86

JM 119

KO 117

KL 109

MQ 115

LP 118

QDEST 134

OP 136

PDEST 130

Worklist

Dijkstra algorithm

DEPDEST

16

40

19

12

19

J

28

34

I14

17

O33

25

Q30

P32

F24

28

D

E

19

31

G22

A

B

C

2125

23

H

K

35

26 L

M18

29







FL350

FL310

FL280

FL260

FL240

FL220

Maximum flightlevel

Optimum flightlevel



If


DIJKSTRAS ALGORITHM



Approach Greedy



























SID


SIDs and STARs



Wind forecast



calculation


runway to runway

STAR



Enroute alternate 1

Enroute alternate 3

Escape route

Flight direction

Terrain

Continuing point

No-Return point

Diversion area




Decision points




Enroute alternate 2




NP-complete problem









+ time allocation

V

L

T








HOW BIG DATA MINING





Ant-Colony

Branch amp Bound


Evolution Strategy

Dynamic Programming

Simulated Annealing

Tabu-Search

Particle Swarm

HOW TO USE BIG DATA



optimization






efficiency

Lower Airspace






euro

AOC



spaces


way through the AOC

accuracy space

NM ATC



wide



parameters

accuracy space





Needs




Airspace

User

ATC(Cost efficient)






INCIDENT ANALYSIS

INCIDENT ANALYSIS


72






77

PROOF OF MODEL

78


79

CHANGE MANAGEMENT

80


GAP ANALYSIS

82






automation tools














5


City B

AOC1

AOC2

ANSP1

ANSP2

ANSP3

ANSP4

ANSP1




6


TRAJECTORY RELATED

INFORMATION

AOC1

AOC2

ANSP1

ANSP2

ANSP3

ANSP1

ANSP4

7

TRAJECTORY RELATED

INFORMATION


TP2

TPI

TP1

TPP

TP6

TPN

TP3

TPR

TP4

TPK

TP5

TPL

TPH

CDampR

ASAS

FMS

AMANFDPS

FMS

FMS

ATFM




FP=Flight Planning






(position speed

weighthellip)


Environmental

Conditions

Pilot

Real World


Flight Commands

amp Guidance

Modes

Flight

Intent

Flight

Plan

Tactical

Amendments to

Flight Plan

Airborne

Automation

System

Actual

Trajectory

Aircraft

Predicted

Trajectory

Trajectory

Computation

Infrastructure

Aircraft

Intent

Intent

Generation

Infrastructure

Initial

Conditions


AT or ABOVE FL290



information

Flight

Intent

Airborne

Predicted

Trajectory


Flight

Intent

Ground

Predicted

Trajectory

Trajectory

Computation

Infrastructure

(1)

Aircraft

Intent

Intent

Generation

Infrastructure

(1)

Airborne TP

Trajectory

Computation

Infrastructure

(2)

Aircraft

Intent

Intent

Generation

Infrastructure

(2)

Ground TP

Aircraft Intent

information

Flight Intent

Information














11

Next generation

FMS

AOC 2

ATFM DST

FMS

AOC 1

FDPS

AMAN DST

Next

Generation

FDPS

Air-Air

Air-Ground

Ground-Ground


12


AIRCRAFT INTENT

TP2

TPI

TPP

TPR

TPK

TP5

TPL

TPH

Translator

I-5

Translator

R-5

Translator

2-K

Translator

R-2

Translator

2-5

Translator

I-2

Translator

H-5

Translator

R-P


Translator

K-P

Translator

5-K

Translator

I-R

Translator

5-P

Translator

L-5

Translator

I-H

Translator

H-L

Translator

R-K

Translator

L-P


13

TP2

TPI

TPP

TPR

TPK

TP5

TPL

TPH

Translator

L-AIDL

AIDL

Translator

5-AIDL

Translator

P-AIDL

Translator

K-AIDL

Translator

R-AIDL

Translator

2-AIDL

Translator

H-AIDL

Translator

I-AIDL

N TRANSLATORS


externalinternal

Constraints amp

Rules

Aeronautical

Nav Data

Weather

Data

Basic Flight

Data amp

Schedule

Route Type amp

Optimization

Settings

Aircraft

Performance

Data

Business Rules

euroFlight

Number

City Pair

Alternate

ADES

DOF STD

Fuel Policy AC Type

AC

Equipment

AC

Envelope

Payload

Payload -

Range

Wind

Condition

Air Pressure

Air Temp

Natural

Hazards

Stat Dyn

Routes

Fix Free

Route

Opt Criteria

Cost Index

Traffic

Rights

RNAV Rules

NOTAM

TFR

(eg RAD)

Terrain

Clearance

Terminal

Procedures

DCT

Connection

Airport

Definition

Flight

connectivity

Human Req

Time Costs

Business

Targets

Business

Constraints

Conditional

Routes

DATA TYPES

bull METARTAF



BECMG 01030106 SCT035

TEMPO 01080112 04015G25KT


Weather

Data

METAR EXPLAINED


SLP176 P0002 T10171017


















DATA TYPES



Aeronautical

Nav Data

SID

STAR

DATA TYPES

bull Airspace rules

ndash Eg seperation

Constraints amp

Rules

DATA TYPES

bull Cost Index



Route Type amp

Optimization

Settings

COST DEFINITION

COST INDEX EXAMPLE


FIDL EXAMPLE

INPUTS







STARs and SIDs

bull ie ATFM policy


(APM)

bull Based on BADA



FIDL EXAMPLE



FIDL EXAMPLE



FIDL EXAMPLE



FIDL EXAMPLE


DATA TYPES

bull Flight Plan





Basic Flight

Data amp

Schedule









044840DCT160597V490001N0083550E76N 045435DCT75623V491355N0083323E88N












042020LSTSA40P042115ERSA470300N0085520E470644N0085449E160160379386








































regulation system






tool








Filed Flight Plan

CDM

Header

Point Profile

Airspace Profile

Circle Intersection

Profile

RTFM Profile

CTFM Profile

CFP Profile

FTFM Profile






DATA TYPES




bull optimization

Aircraft

Performance

Data



High-lift device















High-lift device





DATA TYPES


ndash Cost Index



Business Rules

euro



A

B

C

DEP

DEP

DEP

21

25

23

A

A

E

B

52

40

CG 45

B

B

E

F

49

53

G

G

F

J

73

79

E

E

K

H

84

75

F

F

H

I

70

67

I

I

L

M

96

85

HL 86

JM 119

KO 117

KL 109

MQ 115

LP 118

QDEST 134

OP 136

PDEST 130

Worklist

Dijkstra algorithm

DEPDEST

16

40

19

12

19

J

28

34

I14

17

O33

25

Q30

P32

F24

28

D

E

19

31

G22

A

B

C

2125

23

H

K

35

26 L

M18

29







FL350

FL310

FL280

FL260

FL240

FL220

Maximum flightlevel

Optimum flightlevel



If


DIJKSTRAS ALGORITHM



Approach Greedy



























SID


SIDs and STARs



Wind forecast



calculation


runway to runway

STAR



Enroute alternate 1

Enroute alternate 3

Escape route

Flight direction

Terrain

Continuing point

No-Return point

Diversion area




Decision points




Enroute alternate 2




NP-complete problem









+ time allocation

V

L

T








HOW BIG DATA MINING





Ant-Colony

Branch amp Bound


Evolution Strategy

Dynamic Programming

Simulated Annealing

Tabu-Search

Particle Swarm

HOW TO USE BIG DATA



optimization






efficiency

Lower Airspace






euro

AOC



spaces


way through the AOC

accuracy space

NM ATC



wide



parameters

accuracy space





Needs




Airspace

User

ATC(Cost efficient)






INCIDENT ANALYSIS

INCIDENT ANALYSIS


72






77

PROOF OF MODEL

78


79

CHANGE MANAGEMENT

80


GAP ANALYSIS

82









5


City B

AOC1

AOC2

ANSP1

ANSP2

ANSP3

ANSP4

ANSP1




6


TRAJECTORY RELATED

INFORMATION

AOC1

AOC2

ANSP1

ANSP2

ANSP3

ANSP1

ANSP4

7

TRAJECTORY RELATED

INFORMATION


TP2

TPI

TP1

TPP

TP6

TPN

TP3

TPR

TP4

TPK

TP5

TPL

TPH

CDampR

ASAS

FMS

AMANFDPS

FMS

FMS

ATFM




FP=Flight Planning






(position speed

weighthellip)


Environmental

Conditions

Pilot

Real World


Flight Commands

amp Guidance

Modes

Flight

Intent

Flight

Plan

Tactical

Amendments to

Flight Plan

Airborne

Automation

System

Actual

Trajectory

Aircraft

Predicted

Trajectory

Trajectory

Computation

Infrastructure

Aircraft

Intent

Intent

Generation

Infrastructure

Initial

Conditions


AT or ABOVE FL290



information

Flight

Intent

Airborne

Predicted

Trajectory


Flight

Intent

Ground

Predicted

Trajectory

Trajectory

Computation

Infrastructure

(1)

Aircraft

Intent

Intent

Generation

Infrastructure

(1)

Airborne TP

Trajectory

Computation

Infrastructure

(2)

Aircraft

Intent

Intent

Generation

Infrastructure

(2)

Ground TP

Aircraft Intent

information

Flight Intent

Information














11

Next generation

FMS

AOC 2

ATFM DST

FMS

AOC 1

FDPS

AMAN DST

Next

Generation

FDPS

Air-Air

Air-Ground

Ground-Ground


12


AIRCRAFT INTENT

TP2

TPI

TPP

TPR

TPK

TP5

TPL

TPH

Translator

I-5

Translator

R-5

Translator

2-K

Translator

R-2

Translator

2-5

Translator

I-2

Translator

H-5

Translator

R-P


Translator

K-P

Translator

5-K

Translator

I-R

Translator

5-P

Translator

L-5

Translator

I-H

Translator

H-L

Translator

R-K

Translator

L-P


13

TP2

TPI

TPP

TPR

TPK

TP5

TPL

TPH

Translator

L-AIDL

AIDL

Translator

5-AIDL

Translator

P-AIDL

Translator

K-AIDL

Translator

R-AIDL

Translator

2-AIDL

Translator

H-AIDL

Translator

I-AIDL

N TRANSLATORS


externalinternal

Constraints amp

Rules

Aeronautical

Nav Data

Weather

Data

Basic Flight

Data amp

Schedule

Route Type amp

Optimization

Settings

Aircraft

Performance

Data

Business Rules

euroFlight

Number

City Pair

Alternate

ADES

DOF STD

Fuel Policy AC Type

AC

Equipment

AC

Envelope

Payload

Payload -

Range

Wind

Condition

Air Pressure

Air Temp

Natural

Hazards

Stat Dyn

Routes

Fix Free

Route

Opt Criteria

Cost Index

Traffic

Rights

RNAV Rules

NOTAM

TFR

(eg RAD)

Terrain

Clearance

Terminal

Procedures

DCT

Connection

Airport

Definition

Flight

connectivity

Human Req

Time Costs

Business

Targets

Business

Constraints

Conditional

Routes

DATA TYPES

bull METARTAF



BECMG 01030106 SCT035

TEMPO 01080112 04015G25KT


Weather

Data

METAR EXPLAINED


SLP176 P0002 T10171017


















DATA TYPES



Aeronautical

Nav Data

SID

STAR

DATA TYPES

bull Airspace rules

ndash Eg seperation

Constraints amp

Rules

DATA TYPES

bull Cost Index



Route Type amp

Optimization

Settings

COST DEFINITION

COST INDEX EXAMPLE


FIDL EXAMPLE

INPUTS







STARs and SIDs

bull ie ATFM policy


(APM)

bull Based on BADA



FIDL EXAMPLE



FIDL EXAMPLE



FIDL EXAMPLE



FIDL EXAMPLE


DATA TYPES

bull Flight Plan





Basic Flight

Data amp

Schedule









044840DCT160597V490001N0083550E76N 045435DCT75623V491355N0083323E88N












042020LSTSA40P042115ERSA470300N0085520E470644N0085449E160160379386








































regulation system






tool








Filed Flight Plan

CDM

Header

Point Profile

Airspace Profile

Circle Intersection

Profile

RTFM Profile

CTFM Profile

CFP Profile

FTFM Profile






DATA TYPES




bull optimization

Aircraft

Performance

Data



High-lift device















High-lift device





DATA TYPES


ndash Cost Index



Business Rules

euro



A

B

C

DEP

DEP

DEP

21

25

23

A

A

E

B

52

40

CG 45

B

B

E

F

49

53

G

G

F

J

73

79

E

E

K

H

84

75

F

F

H

I

70

67

I

I

L

M

96

85

HL 86

JM 119

KO 117

KL 109

MQ 115

LP 118

QDEST 134

OP 136

PDEST 130

Worklist

Dijkstra algorithm

DEPDEST

16

40

19

12

19

J

28

34

I14

17

O33

25

Q30

P32

F24

28

D

E

19

31

G22

A

B

C

2125

23

H

K

35

26 L

M18

29







FL350

FL310

FL280

FL260

FL240

FL220

Maximum flightlevel

Optimum flightlevel



If


DIJKSTRAS ALGORITHM



Approach Greedy



























SID


SIDs and STARs



Wind forecast



calculation


runway to runway

STAR



Enroute alternate 1

Enroute alternate 3

Escape route

Flight direction

Terrain

Continuing point

No-Return point

Diversion area




Decision points




Enroute alternate 2




NP-complete problem









+ time allocation

V

L

T








HOW BIG DATA MINING





Ant-Colony

Branch amp Bound


Evolution Strategy

Dynamic Programming

Simulated Annealing

Tabu-Search

Particle Swarm

HOW TO USE BIG DATA



optimization






efficiency

Lower Airspace






euro

AOC



spaces


way through the AOC

accuracy space

NM ATC



wide



parameters

accuracy space





Needs




Airspace

User

ATC(Cost efficient)






INCIDENT ANALYSIS

INCIDENT ANALYSIS


72






77

PROOF OF MODEL

78


79

CHANGE MANAGEMENT

80


GAP ANALYSIS

82


6


TRAJECTORY RELATED

INFORMATION

AOC1

AOC2

ANSP1

ANSP2

ANSP3

ANSP1

ANSP4

7

TRAJECTORY RELATED

INFORMATION


TP2

TPI

TP1

TPP

TP6

TPN

TP3

TPR

TP4

TPK

TP5

TPL

TPH

CDampR

ASAS

FMS

AMANFDPS

FMS

FMS

ATFM




FP=Flight Planning






(position speed

weighthellip)


Environmental

Conditions

Pilot

Real World


Flight Commands

amp Guidance

Modes

Flight

Intent

Flight

Plan

Tactical

Amendments to

Flight Plan

Airborne

Automation

System

Actual

Trajectory

Aircraft

Predicted

Trajectory

Trajectory

Computation

Infrastructure

Aircraft

Intent

Intent

Generation

Infrastructure

Initial

Conditions


AT or ABOVE FL290



information

Flight

Intent

Airborne

Predicted

Trajectory


Flight

Intent

Ground

Predicted

Trajectory

Trajectory

Computation

Infrastructure

(1)

Aircraft

Intent

Intent

Generation

Infrastructure

(1)

Airborne TP

Trajectory

Computation

Infrastructure

(2)

Aircraft

Intent

Intent

Generation

Infrastructure

(2)

Ground TP

Aircraft Intent

information

Flight Intent

Information














11

Next generation

FMS

AOC 2

ATFM DST

FMS

AOC 1

FDPS

AMAN DST

Next

Generation

FDPS

Air-Air

Air-Ground

Ground-Ground


12


AIRCRAFT INTENT

TP2

TPI

TPP

TPR

TPK

TP5

TPL

TPH

Translator

I-5

Translator

R-5

Translator

2-K

Translator

R-2

Translator

2-5

Translator

I-2

Translator

H-5

Translator

R-P


Translator

K-P

Translator

5-K

Translator

I-R

Translator

5-P

Translator

L-5

Translator

I-H

Translator

H-L

Translator

R-K

Translator

L-P


13

TP2

TPI

TPP

TPR

TPK

TP5

TPL

TPH

Translator

L-AIDL

AIDL

Translator

5-AIDL

Translator

P-AIDL

Translator

K-AIDL

Translator

R-AIDL

Translator

2-AIDL

Translator

H-AIDL

Translator

I-AIDL

N TRANSLATORS


externalinternal

Constraints amp

Rules

Aeronautical

Nav Data

Weather

Data

Basic Flight

Data amp

Schedule

Route Type amp

Optimization

Settings

Aircraft

Performance

Data

Business Rules

euroFlight

Number

City Pair

Alternate

ADES

DOF STD

Fuel Policy AC Type

AC

Equipment

AC

Envelope

Payload

Payload -

Range

Wind

Condition

Air Pressure

Air Temp

Natural

Hazards

Stat Dyn

Routes

Fix Free

Route

Opt Criteria

Cost Index

Traffic

Rights

RNAV Rules

NOTAM

TFR

(eg RAD)

Terrain

Clearance

Terminal

Procedures

DCT

Connection

Airport

Definition

Flight

connectivity

Human Req

Time Costs

Business

Targets

Business

Constraints

Conditional

Routes

DATA TYPES

bull METARTAF



BECMG 01030106 SCT035

TEMPO 01080112 04015G25KT


Weather

Data

METAR EXPLAINED


SLP176 P0002 T10171017


















DATA TYPES



Aeronautical

Nav Data

SID

STAR

DATA TYPES

bull Airspace rules

ndash Eg seperation

Constraints amp

Rules

DATA TYPES

bull Cost Index



Route Type amp

Optimization

Settings

COST DEFINITION

COST INDEX EXAMPLE


FIDL EXAMPLE

INPUTS







STARs and SIDs

bull ie ATFM policy


(APM)

bull Based on BADA



FIDL EXAMPLE



FIDL EXAMPLE



FIDL EXAMPLE



FIDL EXAMPLE


DATA TYPES

bull Flight Plan





Basic Flight

Data amp

Schedule









044840DCT160597V490001N0083550E76N 045435DCT75623V491355N0083323E88N












042020LSTSA40P042115ERSA470300N0085520E470644N0085449E160160379386








































regulation system






tool








Filed Flight Plan

CDM

Header

Point Profile

Airspace Profile

Circle Intersection

Profile

RTFM Profile

CTFM Profile

CFP Profile

FTFM Profile






DATA TYPES




bull optimization

Aircraft

Performance

Data



High-lift device















High-lift device





DATA TYPES


ndash Cost Index



Business Rules

euro



A

B

C

DEP

DEP

DEP

21

25

23

A

A

E

B

52

40

CG 45

B

B

E

F

49

53

G

G

F

J

73

79

E

E

K

H

84

75

F

F

H

I

70

67

I

I

L

M

96

85

HL 86

JM 119

KO 117

KL 109

MQ 115

LP 118

QDEST 134

OP 136

PDEST 130

Worklist

Dijkstra algorithm

DEPDEST

16

40

19

12

19

J

28

34

I14

17

O33

25

Q30

P32

F24

28

D

E

19

31

G22

A

B

C

2125

23

H

K

35

26 L

M18

29







FL350

FL310

FL280

FL260

FL240

FL220

Maximum flightlevel

Optimum flightlevel



If


DIJKSTRAS ALGORITHM



Approach Greedy



























SID


SIDs and STARs



Wind forecast



calculation


runway to runway

STAR



Enroute alternate 1

Enroute alternate 3

Escape route

Flight direction

Terrain

Continuing point

No-Return point

Diversion area




Decision points




Enroute alternate 2




NP-complete problem









+ time allocation

V

L

T








HOW BIG DATA MINING





Ant-Colony

Branch amp Bound


Evolution Strategy

Dynamic Programming

Simulated Annealing

Tabu-Search

Particle Swarm

HOW TO USE BIG DATA



optimization






efficiency

Lower Airspace






euro

AOC



spaces


way through the AOC

accuracy space

NM ATC



wide



parameters

accuracy space





Needs




Airspace

User

ATC(Cost efficient)






INCIDENT ANALYSIS

INCIDENT ANALYSIS


72






77

PROOF OF MODEL

78


79

CHANGE MANAGEMENT

80


GAP ANALYSIS

82


7

TRAJECTORY RELATED

INFORMATION


TP2

TPI

TP1

TPP

TP6

TPN

TP3

TPR

TP4

TPK

TP5

TPL

TPH

CDampR

ASAS

FMS

AMANFDPS

FMS

FMS

ATFM




FP=Flight Planning






(position speed

weighthellip)


Environmental

Conditions

Pilot

Real World


Flight Commands

amp Guidance

Modes

Flight

Intent

Flight

Plan

Tactical

Amendments to

Flight Plan

Airborne

Automation

System

Actual

Trajectory

Aircraft

Predicted

Trajectory

Trajectory

Computation

Infrastructure

Aircraft

Intent

Intent

Generation

Infrastructure

Initial

Conditions


AT or ABOVE FL290



information

Flight

Intent

Airborne

Predicted

Trajectory


Flight

Intent

Ground

Predicted

Trajectory

Trajectory

Computation

Infrastructure

(1)

Aircraft

Intent

Intent

Generation

Infrastructure

(1)

Airborne TP

Trajectory

Computation

Infrastructure

(2)

Aircraft

Intent

Intent

Generation

Infrastructure

(2)

Ground TP

Aircraft Intent

information

Flight Intent

Information














11

Next generation

FMS

AOC 2

ATFM DST

FMS

AOC 1

FDPS

AMAN DST

Next

Generation

FDPS

Air-Air

Air-Ground

Ground-Ground


12


AIRCRAFT INTENT

TP2

TPI

TPP

TPR

TPK

TP5

TPL

TPH

Translator

I-5

Translator

R-5

Translator

2-K

Translator

R-2

Translator

2-5

Translator

I-2

Translator

H-5

Translator

R-P


Translator

K-P

Translator

5-K

Translator

I-R

Translator

5-P

Translator

L-5

Translator

I-H

Translator

H-L

Translator

R-K

Translator

L-P


13

TP2

TPI

TPP

TPR

TPK

TP5

TPL

TPH

Translator

L-AIDL

AIDL

Translator

5-AIDL

Translator

P-AIDL

Translator

K-AIDL

Translator

R-AIDL

Translator

2-AIDL

Translator

H-AIDL

Translator

I-AIDL

N TRANSLATORS


externalinternal

Constraints amp

Rules

Aeronautical

Nav Data

Weather

Data

Basic Flight

Data amp

Schedule

Route Type amp

Optimization

Settings

Aircraft

Performance

Data

Business Rules

euroFlight

Number

City Pair

Alternate

ADES

DOF STD

Fuel Policy AC Type

AC

Equipment

AC

Envelope

Payload

Payload -

Range

Wind

Condition

Air Pressure

Air Temp

Natural

Hazards

Stat Dyn

Routes

Fix Free

Route

Opt Criteria

Cost Index

Traffic

Rights

RNAV Rules

NOTAM

TFR

(eg RAD)

Terrain

Clearance

Terminal

Procedures

DCT

Connection

Airport

Definition

Flight

connectivity

Human Req

Time Costs

Business

Targets

Business

Constraints

Conditional

Routes

DATA TYPES

bull METARTAF



BECMG 01030106 SCT035

TEMPO 01080112 04015G25KT


Weather

Data

METAR EXPLAINED


SLP176 P0002 T10171017


















DATA TYPES



Aeronautical

Nav Data

SID

STAR

DATA TYPES

bull Airspace rules

ndash Eg seperation

Constraints amp

Rules

DATA TYPES

bull Cost Index



Route Type amp

Optimization

Settings

COST DEFINITION

COST INDEX EXAMPLE


FIDL EXAMPLE

INPUTS







STARs and SIDs

bull ie ATFM policy


(APM)

bull Based on BADA



FIDL EXAMPLE



FIDL EXAMPLE



FIDL EXAMPLE



FIDL EXAMPLE


DATA TYPES

bull Flight Plan





Basic Flight

Data amp

Schedule









044840DCT160597V490001N0083550E76N 045435DCT75623V491355N0083323E88N












042020LSTSA40P042115ERSA470300N0085520E470644N0085449E160160379386








































regulation system






tool








Filed Flight Plan

CDM

Header

Point Profile

Airspace Profile

Circle Intersection

Profile

RTFM Profile

CTFM Profile

CFP Profile

FTFM Profile






DATA TYPES




bull optimization

Aircraft

Performance

Data



High-lift device















High-lift device





DATA TYPES


ndash Cost Index



Business Rules

euro



A

B

C

DEP

DEP

DEP

21

25

23

A

A

E

B

52

40

CG 45

B

B

E

F

49

53

G

G

F

J

73

79

E

E

K

H

84

75

F

F

H

I

70

67

I

I

L

M

96

85

HL 86

JM 119

KO 117

KL 109

MQ 115

LP 118

QDEST 134

OP 136

PDEST 130

Worklist

Dijkstra algorithm

DEPDEST

16

40

19

12

19

J

28

34

I14

17

O33

25

Q30

P32

F24

28

D

E

19

31

G22

A

B

C

2125

23

H

K

35

26 L

M18

29







FL350

FL310

FL280

FL260

FL240

FL220

Maximum flightlevel

Optimum flightlevel



If


DIJKSTRAS ALGORITHM



Approach Greedy



























SID


SIDs and STARs



Wind forecast



calculation


runway to runway

STAR



Enroute alternate 1

Enroute alternate 3

Escape route

Flight direction

Terrain

Continuing point

No-Return point

Diversion area




Decision points




Enroute alternate 2




NP-complete problem









+ time allocation

V

L

T








HOW BIG DATA MINING





Ant-Colony

Branch amp Bound


Evolution Strategy

Dynamic Programming

Simulated Annealing

Tabu-Search

Particle Swarm

HOW TO USE BIG DATA



optimization






efficiency

Lower Airspace






euro

AOC



spaces


way through the AOC

accuracy space

NM ATC



wide



parameters

accuracy space





Needs




Airspace

User

ATC(Cost efficient)






INCIDENT ANALYSIS

INCIDENT ANALYSIS


72






77

PROOF OF MODEL

78


79

CHANGE MANAGEMENT

80


GAP ANALYSIS

82



(position speed

weighthellip)


Environmental

Conditions

Pilot

Real World


Flight Commands

amp Guidance

Modes

Flight

Intent

Flight

Plan

Tactical

Amendments to

Flight Plan

Airborne

Automation

System

Actual

Trajectory

Aircraft

Predicted

Trajectory

Trajectory

Computation

Infrastructure

Aircraft

Intent

Intent

Generation

Infrastructure

Initial

Conditions


AT or ABOVE FL290



information

Flight

Intent

Airborne

Predicted

Trajectory


Flight

Intent

Ground

Predicted

Trajectory

Trajectory

Computation

Infrastructure

(1)

Aircraft

Intent

Intent

Generation

Infrastructure

(1)

Airborne TP

Trajectory

Computation

Infrastructure

(2)

Aircraft

Intent

Intent

Generation

Infrastructure

(2)

Ground TP

Aircraft Intent

information

Flight Intent

Information














11

Next generation

FMS

AOC 2

ATFM DST

FMS

AOC 1

FDPS

AMAN DST

Next

Generation

FDPS

Air-Air

Air-Ground

Ground-Ground


12


AIRCRAFT INTENT

TP2

TPI

TPP

TPR

TPK

TP5

TPL

TPH

Translator

I-5

Translator

R-5

Translator

2-K

Translator

R-2

Translator

2-5

Translator

I-2

Translator

H-5

Translator

R-P


Translator

K-P

Translator

5-K

Translator

I-R

Translator

5-P

Translator

L-5

Translator

I-H

Translator

H-L

Translator

R-K

Translator

L-P


13

TP2

TPI

TPP

TPR

TPK

TP5

TPL

TPH

Translator

L-AIDL

AIDL

Translator

5-AIDL

Translator

P-AIDL

Translator

K-AIDL

Translator

R-AIDL

Translator

2-AIDL

Translator

H-AIDL

Translator

I-AIDL

N TRANSLATORS


externalinternal

Constraints amp

Rules

Aeronautical

Nav Data

Weather

Data

Basic Flight

Data amp

Schedule

Route Type amp

Optimization

Settings

Aircraft

Performance

Data

Business Rules

euroFlight

Number

City Pair

Alternate

ADES

DOF STD

Fuel Policy AC Type

AC

Equipment

AC

Envelope

Payload

Payload -

Range

Wind

Condition

Air Pressure

Air Temp

Natural

Hazards

Stat Dyn

Routes

Fix Free

Route

Opt Criteria

Cost Index

Traffic

Rights

RNAV Rules

NOTAM

TFR

(eg RAD)

Terrain

Clearance

Terminal

Procedures

DCT

Connection

Airport

Definition

Flight

connectivity

Human Req

Time Costs

Business

Targets

Business

Constraints

Conditional

Routes

DATA TYPES

bull METARTAF



BECMG 01030106 SCT035

TEMPO 01080112 04015G25KT


Weather

Data

METAR EXPLAINED


SLP176 P0002 T10171017


















DATA TYPES



Aeronautical

Nav Data

SID

STAR

DATA TYPES

bull Airspace rules

ndash Eg seperation

Constraints amp

Rules

DATA TYPES

bull Cost Index



Route Type amp

Optimization

Settings

COST DEFINITION

COST INDEX EXAMPLE


FIDL EXAMPLE

INPUTS







STARs and SIDs

bull ie ATFM policy


(APM)

bull Based on BADA



FIDL EXAMPLE



FIDL EXAMPLE



FIDL EXAMPLE



FIDL EXAMPLE


DATA TYPES

bull Flight Plan





Basic Flight

Data amp

Schedule









044840DCT160597V490001N0083550E76N 045435DCT75623V491355N0083323E88N












042020LSTSA40P042115ERSA470300N0085520E470644N0085449E160160379386








































regulation system






tool








Filed Flight Plan

CDM

Header

Point Profile

Airspace Profile

Circle Intersection

Profile

RTFM Profile

CTFM Profile

CFP Profile

FTFM Profile






DATA TYPES




bull optimization

Aircraft

Performance

Data



High-lift device















High-lift device





DATA TYPES


ndash Cost Index



Business Rules

euro



A

B

C

DEP

DEP

DEP

21

25

23

A

A

E

B

52

40

CG 45

B

B

E

F

49

53

G

G

F

J

73

79

E

E

K

H

84

75

F

F

H

I

70

67

I

I

L

M

96

85

HL 86

JM 119

KO 117

KL 109

MQ 115

LP 118

QDEST 134

OP 136

PDEST 130

Worklist

Dijkstra algorithm

DEPDEST

16

40

19

12

19

J

28

34

I14

17

O33

25

Q30

P32

F24

28

D

E

19

31

G22

A

B

C

2125

23

H

K

35

26 L

M18

29







FL350

FL310

FL280

FL260

FL240

FL220

Maximum flightlevel

Optimum flightlevel



If


DIJKSTRAS ALGORITHM



Approach Greedy



























SID


SIDs and STARs



Wind forecast



calculation


runway to runway

STAR



Enroute alternate 1

Enroute alternate 3

Escape route

Flight direction

Terrain

Continuing point

No-Return point

Diversion area




Decision points




Enroute alternate 2




NP-complete problem









+ time allocation

V

L

T








HOW BIG DATA MINING





Ant-Colony

Branch amp Bound


Evolution Strategy

Dynamic Programming

Simulated Annealing

Tabu-Search

Particle Swarm

HOW TO USE BIG DATA



optimization






efficiency

Lower Airspace






euro

AOC



spaces


way through the AOC

accuracy space

NM ATC



wide



parameters

accuracy space





Needs




Airspace

User

ATC(Cost efficient)






INCIDENT ANALYSIS

INCIDENT ANALYSIS


72






77

PROOF OF MODEL

78


79

CHANGE MANAGEMENT

80


GAP ANALYSIS

82




information

Flight

Intent

Airborne

Predicted

Trajectory


Flight

Intent

Ground

Predicted

Trajectory

Trajectory

Computation

Infrastructure

(1)

Aircraft

Intent

Intent

Generation

Infrastructure

(1)

Airborne TP

Trajectory

Computation

Infrastructure

(2)

Aircraft

Intent

Intent

Generation

Infrastructure

(2)

Ground TP

Aircraft Intent

information

Flight Intent

Information














11

Next generation

FMS

AOC 2

ATFM DST

FMS

AOC 1

FDPS

AMAN DST

Next

Generation

FDPS

Air-Air

Air-Ground

Ground-Ground


12


AIRCRAFT INTENT

TP2

TPI

TPP

TPR

TPK

TP5

TPL

TPH

Translator

I-5

Translator

R-5

Translator

2-K

Translator

R-2

Translator

2-5

Translator

I-2

Translator

H-5

Translator

R-P


Translator

K-P

Translator

5-K

Translator

I-R

Translator

5-P

Translator

L-5

Translator

I-H

Translator

H-L

Translator

R-K

Translator

L-P


13

TP2

TPI

TPP

TPR

TPK

TP5

TPL

TPH

Translator

L-AIDL

AIDL

Translator

5-AIDL

Translator

P-AIDL

Translator

K-AIDL

Translator

R-AIDL

Translator

2-AIDL

Translator

H-AIDL

Translator

I-AIDL

N TRANSLATORS


externalinternal

Constraints amp

Rules

Aeronautical

Nav Data

Weather

Data

Basic Flight

Data amp

Schedule

Route Type amp

Optimization

Settings

Aircraft

Performance

Data

Business Rules

euroFlight

Number

City Pair

Alternate

ADES

DOF STD

Fuel Policy AC Type

AC

Equipment

AC

Envelope

Payload

Payload -

Range

Wind

Condition

Air Pressure

Air Temp

Natural

Hazards

Stat Dyn

Routes

Fix Free

Route

Opt Criteria

Cost Index

Traffic

Rights

RNAV Rules

NOTAM

TFR

(eg RAD)

Terrain

Clearance

Terminal

Procedures

DCT

Connection

Airport

Definition

Flight

connectivity

Human Req

Time Costs

Business

Targets

Business

Constraints

Conditional

Routes

DATA TYPES

bull METARTAF



BECMG 01030106 SCT035

TEMPO 01080112 04015G25KT


Weather

Data

METAR EXPLAINED


SLP176 P0002 T10171017


















DATA TYPES



Aeronautical

Nav Data

SID

STAR

DATA TYPES

bull Airspace rules

ndash Eg seperation

Constraints amp

Rules

DATA TYPES

bull Cost Index



Route Type amp

Optimization

Settings

COST DEFINITION

COST INDEX EXAMPLE


FIDL EXAMPLE

INPUTS







STARs and SIDs

bull ie ATFM policy


(APM)

bull Based on BADA



FIDL EXAMPLE



FIDL EXAMPLE



FIDL EXAMPLE



FIDL EXAMPLE


DATA TYPES

bull Flight Plan





Basic Flight

Data amp

Schedule









044840DCT160597V490001N0083550E76N 045435DCT75623V491355N0083323E88N












042020LSTSA40P042115ERSA470300N0085520E470644N0085449E160160379386








































regulation system






tool








Filed Flight Plan

CDM

Header

Point Profile

Airspace Profile

Circle Intersection

Profile

RTFM Profile

CTFM Profile

CFP Profile

FTFM Profile






DATA TYPES




bull optimization

Aircraft

Performance

Data



High-lift device















High-lift device





DATA TYPES


ndash Cost Index



Business Rules

euro



A

B

C

DEP

DEP

DEP

21

25

23

A

A

E

B

52

40

CG 45

B

B

E

F

49

53

G

G

F

J

73

79

E

E

K

H

84

75

F

F

H

I

70

67

I

I

L

M

96

85

HL 86

JM 119

KO 117

KL 109

MQ 115

LP 118

QDEST 134

OP 136

PDEST 130

Worklist

Dijkstra algorithm

DEPDEST

16

40

19

12

19

J

28

34

I14

17

O33

25

Q30

P32

F24

28

D

E

19

31

G22

A

B

C

2125

23

H

K

35

26 L

M18

29







FL350

FL310

FL280

FL260

FL240

FL220

Maximum flightlevel

Optimum flightlevel



If


DIJKSTRAS ALGORITHM



Approach Greedy



























SID


SIDs and STARs



Wind forecast



calculation


runway to runway

STAR



Enroute alternate 1

Enroute alternate 3

Escape route

Flight direction

Terrain

Continuing point

No-Return point

Diversion area




Decision points




Enroute alternate 2




NP-complete problem









+ time allocation

V

L

T








HOW BIG DATA MINING





Ant-Colony

Branch amp Bound


Evolution Strategy

Dynamic Programming

Simulated Annealing

Tabu-Search

Particle Swarm

HOW TO USE BIG DATA



optimization






efficiency

Lower Airspace






euro

AOC



spaces


way through the AOC

accuracy space

NM ATC



wide



parameters

accuracy space





Needs




Airspace

User

ATC(Cost efficient)






INCIDENT ANALYSIS

INCIDENT ANALYSIS


72






77

PROOF OF MODEL

78


79

CHANGE MANAGEMENT

80


GAP ANALYSIS

82














11

Next generation

FMS

AOC 2

ATFM DST

FMS

AOC 1

FDPS

AMAN DST

Next

Generation

FDPS

Air-Air

Air-Ground

Ground-Ground


12


AIRCRAFT INTENT

TP2

TPI

TPP

TPR

TPK

TP5

TPL

TPH

Translator

I-5

Translator

R-5

Translator

2-K

Translator

R-2

Translator

2-5

Translator

I-2

Translator

H-5

Translator

R-P


Translator

K-P

Translator

5-K

Translator

I-R

Translator

5-P

Translator

L-5

Translator

I-H

Translator

H-L

Translator

R-K

Translator

L-P


13

TP2

TPI

TPP

TPR

TPK

TP5

TPL

TPH

Translator

L-AIDL

AIDL

Translator

5-AIDL

Translator

P-AIDL

Translator

K-AIDL

Translator

R-AIDL

Translator

2-AIDL

Translator

H-AIDL

Translator

I-AIDL

N TRANSLATORS


externalinternal

Constraints amp

Rules

Aeronautical

Nav Data

Weather

Data

Basic Flight

Data amp

Schedule

Route Type amp

Optimization

Settings

Aircraft

Performance

Data

Business Rules

euroFlight

Number

City Pair

Alternate

ADES

DOF STD

Fuel Policy AC Type

AC

Equipment

AC

Envelope

Payload

Payload -

Range

Wind

Condition

Air Pressure

Air Temp

Natural

Hazards

Stat Dyn

Routes

Fix Free

Route

Opt Criteria

Cost Index

Traffic

Rights

RNAV Rules

NOTAM

TFR

(eg RAD)

Terrain

Clearance

Terminal

Procedures

DCT

Connection

Airport

Definition

Flight

connectivity

Human Req

Time Costs

Business

Targets

Business

Constraints

Conditional

Routes

DATA TYPES

bull METARTAF



BECMG 01030106 SCT035

TEMPO 01080112 04015G25KT


Weather

Data

METAR EXPLAINED


SLP176 P0002 T10171017


















DATA TYPES



Aeronautical

Nav Data

SID

STAR

DATA TYPES

bull Airspace rules

ndash Eg seperation

Constraints amp

Rules

DATA TYPES

bull Cost Index



Route Type amp

Optimization

Settings

COST DEFINITION

COST INDEX EXAMPLE


FIDL EXAMPLE

INPUTS







STARs and SIDs

bull ie ATFM policy


(APM)

bull Based on BADA



FIDL EXAMPLE



FIDL EXAMPLE



FIDL EXAMPLE



FIDL EXAMPLE


DATA TYPES

bull Flight Plan





Basic Flight

Data amp

Schedule









044840DCT160597V490001N0083550E76N 045435DCT75623V491355N0083323E88N












042020LSTSA40P042115ERSA470300N0085520E470644N0085449E160160379386








































regulation system






tool








Filed Flight Plan

CDM

Header

Point Profile

Airspace Profile

Circle Intersection

Profile

RTFM Profile

CTFM Profile

CFP Profile

FTFM Profile






DATA TYPES




bull optimization

Aircraft

Performance

Data



High-lift device















High-lift device





DATA TYPES


ndash Cost Index



Business Rules

euro



A

B

C

DEP

DEP

DEP

21

25

23

A

A

E

B

52

40

CG 45

B

B

E

F

49

53

G

G

F

J

73

79

E

E

K

H

84

75

F

F

H

I

70

67

I

I

L

M

96

85

HL 86

JM 119

KO 117

KL 109

MQ 115

LP 118

QDEST 134

OP 136

PDEST 130

Worklist

Dijkstra algorithm

DEPDEST

16

40

19

12

19

J

28

34

I14

17

O33

25

Q30

P32

F24

28

D

E

19

31

G22

A

B

C

2125

23

H

K

35

26 L

M18

29







FL350

FL310

FL280

FL260

FL240

FL220

Maximum flightlevel

Optimum flightlevel



If


DIJKSTRAS ALGORITHM



Approach Greedy



























SID


SIDs and STARs



Wind forecast



calculation


runway to runway

STAR



Enroute alternate 1

Enroute alternate 3

Escape route

Flight direction

Terrain

Continuing point

No-Return point

Diversion area




Decision points




Enroute alternate 2




NP-complete problem









+ time allocation

V

L

T








HOW BIG DATA MINING





Ant-Colony

Branch amp Bound


Evolution Strategy

Dynamic Programming

Simulated Annealing

Tabu-Search

Particle Swarm

HOW TO USE BIG DATA



optimization






efficiency

Lower Airspace






euro

AOC



spaces


way through the AOC

accuracy space

NM ATC



wide



parameters

accuracy space





Needs




Airspace

User

ATC(Cost efficient)






INCIDENT ANALYSIS

INCIDENT ANALYSIS


72






77

PROOF OF MODEL

78


79

CHANGE MANAGEMENT

80


GAP ANALYSIS

82


12


AIRCRAFT INTENT

TP2

TPI

TPP

TPR

TPK

TP5

TPL

TPH

Translator

I-5

Translator

R-5

Translator

2-K

Translator

R-2

Translator

2-5

Translator

I-2

Translator

H-5

Translator

R-P


Translator

K-P

Translator

5-K

Translator

I-R

Translator

5-P

Translator

L-5

Translator

I-H

Translator

H-L

Translator

R-K

Translator

L-P


13

TP2

TPI

TPP

TPR

TPK

TP5

TPL

TPH

Translator

L-AIDL

AIDL

Translator

5-AIDL

Translator

P-AIDL

Translator

K-AIDL

Translator

R-AIDL

Translator

2-AIDL

Translator

H-AIDL

Translator

I-AIDL

N TRANSLATORS


externalinternal

Constraints amp

Rules

Aeronautical

Nav Data

Weather

Data

Basic Flight

Data amp

Schedule

Route Type amp

Optimization

Settings

Aircraft

Performance

Data

Business Rules

euroFlight

Number

City Pair

Alternate

ADES

DOF STD

Fuel Policy AC Type

AC

Equipment

AC

Envelope

Payload

Payload -

Range

Wind

Condition

Air Pressure

Air Temp

Natural

Hazards

Stat Dyn

Routes

Fix Free

Route

Opt Criteria

Cost Index

Traffic

Rights

RNAV Rules

NOTAM

TFR

(eg RAD)

Terrain

Clearance

Terminal

Procedures

DCT

Connection

Airport

Definition

Flight

connectivity

Human Req

Time Costs

Business

Targets

Business

Constraints

Conditional

Routes

DATA TYPES

bull METARTAF



BECMG 01030106 SCT035

TEMPO 01080112 04015G25KT


Weather

Data

METAR EXPLAINED


SLP176 P0002 T10171017


















DATA TYPES



Aeronautical

Nav Data

SID

STAR

DATA TYPES

bull Airspace rules

ndash Eg seperation

Constraints amp

Rules

DATA TYPES

bull Cost Index



Route Type amp

Optimization

Settings

COST DEFINITION

COST INDEX EXAMPLE


FIDL EXAMPLE

INPUTS







STARs and SIDs

bull ie ATFM policy


(APM)

bull Based on BADA



FIDL EXAMPLE



FIDL EXAMPLE



FIDL EXAMPLE



FIDL EXAMPLE


DATA TYPES

bull Flight Plan





Basic Flight

Data amp

Schedule









044840DCT160597V490001N0083550E76N 045435DCT75623V491355N0083323E88N












042020LSTSA40P042115ERSA470300N0085520E470644N0085449E160160379386








































regulation system






tool








Filed Flight Plan

CDM

Header

Point Profile

Airspace Profile

Circle Intersection

Profile

RTFM Profile

CTFM Profile

CFP Profile

FTFM Profile






DATA TYPES




bull optimization

Aircraft

Performance

Data



High-lift device















High-lift device





DATA TYPES


ndash Cost Index



Business Rules

euro



A

B

C

DEP

DEP

DEP

21

25

23

A

A

E

B

52

40

CG 45

B

B

E

F

49

53

G

G

F

J

73

79

E

E

K

H

84

75

F

F

H

I

70

67

I

I

L

M

96

85

HL 86

JM 119

KO 117

KL 109

MQ 115

LP 118

QDEST 134

OP 136

PDEST 130

Worklist

Dijkstra algorithm

DEPDEST

16

40

19

12

19

J

28

34

I14

17

O33

25

Q30

P32

F24

28

D

E

19

31

G22

A

B

C

2125

23

H

K

35

26 L

M18

29







FL350

FL310

FL280

FL260

FL240

FL220

Maximum flightlevel

Optimum flightlevel



If


DIJKSTRAS ALGORITHM



Approach Greedy



























SID


SIDs and STARs



Wind forecast



calculation


runway to runway

STAR



Enroute alternate 1

Enroute alternate 3

Escape route

Flight direction

Terrain

Continuing point

No-Return point

Diversion area




Decision points




Enroute alternate 2




NP-complete problem









+ time allocation

V

L

T








HOW BIG DATA MINING





Ant-Colony

Branch amp Bound


Evolution Strategy

Dynamic Programming

Simulated Annealing

Tabu-Search

Particle Swarm

HOW TO USE BIG DATA



optimization






efficiency

Lower Airspace






euro

AOC



spaces


way through the AOC

accuracy space

NM ATC



wide



parameters

accuracy space





Needs




Airspace

User

ATC(Cost efficient)






INCIDENT ANALYSIS

INCIDENT ANALYSIS


72






77

PROOF OF MODEL

78


79

CHANGE MANAGEMENT

80


GAP ANALYSIS

82


13

TP2

TPI

TPP

TPR

TPK

TP5

TPL

TPH

Translator

L-AIDL

AIDL

Translator

5-AIDL

Translator

P-AIDL

Translator

K-AIDL

Translator

R-AIDL

Translator

2-AIDL

Translator

H-AIDL

Translator

I-AIDL

N TRANSLATORS


externalinternal

Constraints amp

Rules

Aeronautical

Nav Data

Weather

Data

Basic Flight

Data amp

Schedule

Route Type amp

Optimization

Settings

Aircraft

Performance

Data

Business Rules

euroFlight

Number

City Pair

Alternate

ADES

DOF STD

Fuel Policy AC Type

AC

Equipment

AC

Envelope

Payload

Payload -

Range

Wind

Condition

Air Pressure

Air Temp

Natural

Hazards

Stat Dyn

Routes

Fix Free

Route

Opt Criteria

Cost Index

Traffic

Rights

RNAV Rules

NOTAM

TFR

(eg RAD)

Terrain

Clearance

Terminal

Procedures

DCT

Connection

Airport

Definition

Flight

connectivity

Human Req

Time Costs

Business

Targets

Business

Constraints

Conditional

Routes

DATA TYPES

bull METARTAF



BECMG 01030106 SCT035

TEMPO 01080112 04015G25KT


Weather

Data

METAR EXPLAINED


SLP176 P0002 T10171017


















DATA TYPES



Aeronautical

Nav Data

SID

STAR

DATA TYPES

bull Airspace rules

ndash Eg seperation

Constraints amp

Rules

DATA TYPES

bull Cost Index



Route Type amp

Optimization

Settings

COST DEFINITION

COST INDEX EXAMPLE


FIDL EXAMPLE

INPUTS







STARs and SIDs

bull ie ATFM policy


(APM)

bull Based on BADA



FIDL EXAMPLE



FIDL EXAMPLE



FIDL EXAMPLE



FIDL EXAMPLE


DATA TYPES

bull Flight Plan





Basic Flight

Data amp

Schedule









044840DCT160597V490001N0083550E76N 045435DCT75623V491355N0083323E88N












042020LSTSA40P042115ERSA470300N0085520E470644N0085449E160160379386








































regulation system






tool








Filed Flight Plan

CDM

Header

Point Profile

Airspace Profile

Circle Intersection

Profile

RTFM Profile

CTFM Profile

CFP Profile

FTFM Profile






DATA TYPES




bull optimization

Aircraft

Performance

Data



High-lift device















High-lift device





DATA TYPES


ndash Cost Index



Business Rules

euro



A

B

C

DEP

DEP

DEP

21

25

23

A

A

E

B

52

40

CG 45

B

B

E

F

49

53

G

G

F

J

73

79

E

E

K

H

84

75

F

F

H

I

70

67

I

I

L

M

96

85

HL 86

JM 119

KO 117

KL 109

MQ 115

LP 118

QDEST 134

OP 136

PDEST 130

Worklist

Dijkstra algorithm

DEPDEST

16

40

19

12

19

J

28

34

I14

17

O33

25

Q30

P32

F24

28

D

E

19

31

G22

A

B

C

2125

23

H

K

35

26 L

M18

29







FL350

FL310

FL280

FL260

FL240

FL220

Maximum flightlevel

Optimum flightlevel



If


DIJKSTRAS ALGORITHM



Approach Greedy



























SID


SIDs and STARs



Wind forecast



calculation


runway to runway

STAR



Enroute alternate 1

Enroute alternate 3

Escape route

Flight direction

Terrain

Continuing point

No-Return point

Diversion area




Decision points




Enroute alternate 2




NP-complete problem









+ time allocation

V

L

T








HOW BIG DATA MINING





Ant-Colony

Branch amp Bound


Evolution Strategy

Dynamic Programming

Simulated Annealing

Tabu-Search

Particle Swarm

HOW TO USE BIG DATA



optimization






efficiency

Lower Airspace






euro

AOC



spaces


way through the AOC

accuracy space

NM ATC



wide



parameters

accuracy space





Needs




Airspace

User

ATC(Cost efficient)






INCIDENT ANALYSIS

INCIDENT ANALYSIS


72






77

PROOF OF MODEL

78


79

CHANGE MANAGEMENT

80


GAP ANALYSIS

82


externalinternal

Constraints amp

Rules

Aeronautical

Nav Data

Weather

Data

Basic Flight

Data amp

Schedule

Route Type amp

Optimization

Settings

Aircraft

Performance

Data

Business Rules

euroFlight

Number

City Pair

Alternate

ADES

DOF STD

Fuel Policy AC Type

AC

Equipment

AC

Envelope

Payload

Payload -

Range

Wind

Condition

Air Pressure

Air Temp

Natural

Hazards

Stat Dyn

Routes

Fix Free

Route

Opt Criteria

Cost Index

Traffic

Rights

RNAV Rules

NOTAM

TFR

(eg RAD)

Terrain

Clearance

Terminal

Procedures

DCT

Connection

Airport

Definition

Flight

connectivity

Human Req

Time Costs

Business

Targets

Business

Constraints

Conditional

Routes

DATA TYPES

bull METARTAF



BECMG 01030106 SCT035

TEMPO 01080112 04015G25KT


Weather

Data

METAR EXPLAINED


SLP176 P0002 T10171017


















DATA TYPES



Aeronautical

Nav Data

SID

STAR

DATA TYPES

bull Airspace rules

ndash Eg seperation

Constraints amp

Rules

DATA TYPES

bull Cost Index



Route Type amp

Optimization

Settings

COST DEFINITION

COST INDEX EXAMPLE


FIDL EXAMPLE

INPUTS







STARs and SIDs

bull ie ATFM policy


(APM)

bull Based on BADA



FIDL EXAMPLE



FIDL EXAMPLE



FIDL EXAMPLE



FIDL EXAMPLE


DATA TYPES

bull Flight Plan





Basic Flight

Data amp

Schedule









044840DCT160597V490001N0083550E76N 045435DCT75623V491355N0083323E88N












042020LSTSA40P042115ERSA470300N0085520E470644N0085449E160160379386








































regulation system






tool








Filed Flight Plan

CDM

Header

Point Profile

Airspace Profile

Circle Intersection

Profile

RTFM Profile

CTFM Profile

CFP Profile

FTFM Profile






DATA TYPES




bull optimization

Aircraft

Performance

Data



High-lift device















High-lift device





DATA TYPES


ndash Cost Index



Business Rules

euro



A

B

C

DEP

DEP

DEP

21

25

23

A

A

E

B

52

40

CG 45

B

B

E

F

49

53

G

G

F

J

73

79

E

E

K

H

84

75

F

F

H

I

70

67

I

I

L

M

96

85

HL 86

JM 119

KO 117

KL 109

MQ 115

LP 118

QDEST 134

OP 136

PDEST 130

Worklist

Dijkstra algorithm

DEPDEST

16

40

19

12

19

J

28

34

I14

17

O33

25

Q30

P32

F24

28

D

E

19

31

G22

A

B

C

2125

23

H

K

35

26 L

M18

29







FL350

FL310

FL280

FL260

FL240

FL220

Maximum flightlevel

Optimum flightlevel



If


DIJKSTRAS ALGORITHM



Approach Greedy



























SID


SIDs and STARs



Wind forecast



calculation


runway to runway

STAR



Enroute alternate 1

Enroute alternate 3

Escape route

Flight direction

Terrain

Continuing point

No-Return point

Diversion area




Decision points




Enroute alternate 2




NP-complete problem









+ time allocation

V

L

T








HOW BIG DATA MINING





Ant-Colony

Branch amp Bound


Evolution Strategy

Dynamic Programming

Simulated Annealing

Tabu-Search

Particle Swarm

HOW TO USE BIG DATA



optimization






efficiency

Lower Airspace






euro

AOC



spaces


way through the AOC

accuracy space

NM ATC



wide



parameters

accuracy space





Needs




Airspace

User

ATC(Cost efficient)






INCIDENT ANALYSIS

INCIDENT ANALYSIS


72






77

PROOF OF MODEL

78


79

CHANGE MANAGEMENT

80


GAP ANALYSIS

82


DATA TYPES

bull METARTAF



BECMG 01030106 SCT035

TEMPO 01080112 04015G25KT


Weather

Data

METAR EXPLAINED


SLP176 P0002 T10171017


















DATA TYPES



Aeronautical

Nav Data

SID

STAR

DATA TYPES

bull Airspace rules

ndash Eg seperation

Constraints amp

Rules

DATA TYPES

bull Cost Index



Route Type amp

Optimization

Settings

COST DEFINITION

COST INDEX EXAMPLE


FIDL EXAMPLE

INPUTS







STARs and SIDs

bull ie ATFM policy


(APM)

bull Based on BADA



FIDL EXAMPLE



FIDL EXAMPLE



FIDL EXAMPLE



FIDL EXAMPLE


DATA TYPES

bull Flight Plan





Basic Flight

Data amp

Schedule









044840DCT160597V490001N0083550E76N 045435DCT75623V491355N0083323E88N












042020LSTSA40P042115ERSA470300N0085520E470644N0085449E160160379386








































regulation system






tool








Filed Flight Plan

CDM

Header

Point Profile

Airspace Profile

Circle Intersection

Profile

RTFM Profile

CTFM Profile

CFP Profile

FTFM Profile






DATA TYPES




bull optimization

Aircraft

Performance

Data



High-lift device















High-lift device





DATA TYPES


ndash Cost Index



Business Rules

euro



A

B

C

DEP

DEP

DEP

21

25

23

A

A

E

B

52

40

CG 45

B

B

E

F

49

53

G

G

F

J

73

79

E

E

K

H

84

75

F

F

H

I

70

67

I

I

L

M

96

85

HL 86

JM 119

KO 117

KL 109

MQ 115

LP 118

QDEST 134

OP 136

PDEST 130

Worklist

Dijkstra algorithm

DEPDEST

16

40

19

12

19

J

28

34

I14

17

O33

25

Q30

P32

F24

28

D

E

19

31

G22

A

B

C

2125

23

H

K

35

26 L

M18

29







FL350

FL310

FL280

FL260

FL240

FL220

Maximum flightlevel

Optimum flightlevel



If


DIJKSTRAS ALGORITHM



Approach Greedy



























SID


SIDs and STARs



Wind forecast



calculation


runway to runway

STAR



Enroute alternate 1

Enroute alternate 3

Escape route

Flight direction

Terrain

Continuing point

No-Return point

Diversion area




Decision points




Enroute alternate 2




NP-complete problem









+ time allocation

V

L

T








HOW BIG DATA MINING





Ant-Colony

Branch amp Bound


Evolution Strategy

Dynamic Programming

Simulated Annealing

Tabu-Search

Particle Swarm

HOW TO USE BIG DATA



optimization






efficiency

Lower Airspace






euro

AOC



spaces


way through the AOC

accuracy space

NM ATC



wide



parameters

accuracy space





Needs




Airspace

User

ATC(Cost efficient)






INCIDENT ANALYSIS

INCIDENT ANALYSIS


72






77

PROOF OF MODEL

78


79

CHANGE MANAGEMENT

80


GAP ANALYSIS

82


METAR EXPLAINED


SLP176 P0002 T10171017


















DATA TYPES



Aeronautical

Nav Data

SID

STAR

DATA TYPES

bull Airspace rules

ndash Eg seperation

Constraints amp

Rules

DATA TYPES

bull Cost Index



Route Type amp

Optimization

Settings

COST DEFINITION

COST INDEX EXAMPLE


FIDL EXAMPLE

INPUTS







STARs and SIDs

bull ie ATFM policy


(APM)

bull Based on BADA



FIDL EXAMPLE



FIDL EXAMPLE



FIDL EXAMPLE



FIDL EXAMPLE


DATA TYPES

bull Flight Plan





Basic Flight

Data amp

Schedule









044840DCT160597V490001N0083550E76N 045435DCT75623V491355N0083323E88N












042020LSTSA40P042115ERSA470300N0085520E470644N0085449E160160379386








































regulation system






tool








Filed Flight Plan

CDM

Header

Point Profile

Airspace Profile

Circle Intersection

Profile

RTFM Profile

CTFM Profile

CFP Profile

FTFM Profile






DATA TYPES




bull optimization

Aircraft

Performance

Data



High-lift device















High-lift device





DATA TYPES


ndash Cost Index



Business Rules

euro



A

B

C

DEP

DEP

DEP

21

25

23

A

A

E

B

52

40

CG 45

B

B

E

F

49

53

G

G

F

J

73

79

E

E

K

H

84

75

F

F

H

I

70

67

I

I

L

M

96

85

HL 86

JM 119

KO 117

KL 109

MQ 115

LP 118

QDEST 134

OP 136

PDEST 130

Worklist

Dijkstra algorithm

DEPDEST

16

40

19

12

19

J

28

34

I14

17

O33

25

Q30

P32

F24

28

D

E

19

31

G22

A

B

C

2125

23

H

K

35

26 L

M18

29







FL350

FL310

FL280

FL260

FL240

FL220

Maximum flightlevel

Optimum flightlevel



If


DIJKSTRAS ALGORITHM



Approach Greedy



























SID


SIDs and STARs



Wind forecast



calculation


runway to runway

STAR



Enroute alternate 1

Enroute alternate 3

Escape route

Flight direction

Terrain

Continuing point

No-Return point

Diversion area




Decision points




Enroute alternate 2




NP-complete problem









+ time allocation

V

L

T








HOW BIG DATA MINING





Ant-Colony

Branch amp Bound


Evolution Strategy

Dynamic Programming

Simulated Annealing

Tabu-Search

Particle Swarm

HOW TO USE BIG DATA



optimization






efficiency

Lower Airspace






euro

AOC



spaces


way through the AOC

accuracy space

NM ATC



wide



parameters

accuracy space





Needs




Airspace

User

ATC(Cost efficient)






INCIDENT ANALYSIS

INCIDENT ANALYSIS


72






77

PROOF OF MODEL

78


79

CHANGE MANAGEMENT

80


GAP ANALYSIS

82


DATA TYPES



Aeronautical

Nav Data

SID

STAR

DATA TYPES

bull Airspace rules

ndash Eg seperation

Constraints amp

Rules

DATA TYPES

bull Cost Index



Route Type amp

Optimization

Settings

COST DEFINITION

COST INDEX EXAMPLE


FIDL EXAMPLE

INPUTS







STARs and SIDs

bull ie ATFM policy


(APM)

bull Based on BADA



FIDL EXAMPLE



FIDL EXAMPLE



FIDL EXAMPLE



FIDL EXAMPLE


DATA TYPES

bull Flight Plan





Basic Flight

Data amp

Schedule









044840DCT160597V490001N0083550E76N 045435DCT75623V491355N0083323E88N












042020LSTSA40P042115ERSA470300N0085520E470644N0085449E160160379386








































regulation system






tool








Filed Flight Plan

CDM

Header

Point Profile

Airspace Profile

Circle Intersection

Profile

RTFM Profile

CTFM Profile

CFP Profile

FTFM Profile






DATA TYPES




bull optimization

Aircraft

Performance

Data



High-lift device















High-lift device





DATA TYPES


ndash Cost Index



Business Rules

euro



A

B

C

DEP

DEP

DEP

21

25

23

A

A

E

B

52

40

CG 45

B

B

E

F

49

53

G

G

F

J

73

79

E

E

K

H

84

75

F

F

H

I

70

67

I

I

L

M

96

85

HL 86

JM 119

KO 117

KL 109

MQ 115

LP 118

QDEST 134

OP 136

PDEST 130

Worklist

Dijkstra algorithm

DEPDEST

16

40

19

12

19

J

28

34

I14

17

O33

25

Q30

P32

F24

28

D

E

19

31

G22

A

B

C

2125

23

H

K

35

26 L

M18

29







FL350

FL310

FL280

FL260

FL240

FL220

Maximum flightlevel

Optimum flightlevel



If


DIJKSTRAS ALGORITHM



Approach Greedy



























SID


SIDs and STARs



Wind forecast



calculation


runway to runway

STAR



Enroute alternate 1

Enroute alternate 3

Escape route

Flight direction

Terrain

Continuing point

No-Return point

Diversion area




Decision points




Enroute alternate 2




NP-complete problem









+ time allocation

V

L

T








HOW BIG DATA MINING





Ant-Colony

Branch amp Bound


Evolution Strategy

Dynamic Programming

Simulated Annealing

Tabu-Search

Particle Swarm

HOW TO USE BIG DATA



optimization






efficiency

Lower Airspace






euro

AOC



spaces


way through the AOC

accuracy space

NM ATC



wide



parameters

accuracy space





Needs




Airspace

User

ATC(Cost efficient)






INCIDENT ANALYSIS

INCIDENT ANALYSIS


72






77

PROOF OF MODEL

78


79

CHANGE MANAGEMENT

80


GAP ANALYSIS

82


SID

STAR

DATA TYPES

bull Airspace rules

ndash Eg seperation

Constraints amp

Rules

DATA TYPES

bull Cost Index



Route Type amp

Optimization

Settings

COST DEFINITION

COST INDEX EXAMPLE


FIDL EXAMPLE

INPUTS







STARs and SIDs

bull ie ATFM policy


(APM)

bull Based on BADA



FIDL EXAMPLE



FIDL EXAMPLE



FIDL EXAMPLE



FIDL EXAMPLE


DATA TYPES

bull Flight Plan





Basic Flight

Data amp

Schedule









044840DCT160597V490001N0083550E76N 045435DCT75623V491355N0083323E88N












042020LSTSA40P042115ERSA470300N0085520E470644N0085449E160160379386








































regulation system






tool








Filed Flight Plan

CDM

Header

Point Profile

Airspace Profile

Circle Intersection

Profile

RTFM Profile

CTFM Profile

CFP Profile

FTFM Profile






DATA TYPES




bull optimization

Aircraft

Performance

Data



High-lift device















High-lift device





DATA TYPES


ndash Cost Index



Business Rules

euro



A

B

C

DEP

DEP

DEP

21

25

23

A

A

E

B

52

40

CG 45

B

B

E

F

49

53

G

G

F

J

73

79

E

E

K

H

84

75

F

F

H

I

70

67

I

I

L

M

96

85

HL 86

JM 119

KO 117

KL 109

MQ 115

LP 118

QDEST 134

OP 136

PDEST 130

Worklist

Dijkstra algorithm

DEPDEST

16

40

19

12

19

J

28

34

I14

17

O33

25

Q30

P32

F24

28

D

E

19

31

G22

A

B

C

2125

23

H

K

35

26 L

M18

29







FL350

FL310

FL280

FL260

FL240

FL220

Maximum flightlevel

Optimum flightlevel



If


DIJKSTRAS ALGORITHM



Approach Greedy



























SID


SIDs and STARs



Wind forecast



calculation


runway to runway

STAR



Enroute alternate 1

Enroute alternate 3

Escape route

Flight direction

Terrain

Continuing point

No-Return point

Diversion area




Decision points




Enroute alternate 2




NP-complete problem









+ time allocation

V

L

T








HOW BIG DATA MINING





Ant-Colony

Branch amp Bound


Evolution Strategy

Dynamic Programming

Simulated Annealing

Tabu-Search

Particle Swarm

HOW TO USE BIG DATA



optimization






efficiency

Lower Airspace






euro

AOC



spaces


way through the AOC

accuracy space

NM ATC



wide



parameters

accuracy space





Needs




Airspace

User

ATC(Cost efficient)






INCIDENT ANALYSIS

INCIDENT ANALYSIS


72






77

PROOF OF MODEL

78


79

CHANGE MANAGEMENT

80


GAP ANALYSIS

82


DATA TYPES

bull Airspace rules

ndash Eg seperation

Constraints amp

Rules

DATA TYPES

bull Cost Index



Route Type amp

Optimization

Settings

COST DEFINITION

COST INDEX EXAMPLE


FIDL EXAMPLE

INPUTS







STARs and SIDs

bull ie ATFM policy


(APM)

bull Based on BADA



FIDL EXAMPLE



FIDL EXAMPLE



FIDL EXAMPLE



FIDL EXAMPLE


DATA TYPES

bull Flight Plan





Basic Flight

Data amp

Schedule









044840DCT160597V490001N0083550E76N 045435DCT75623V491355N0083323E88N












042020LSTSA40P042115ERSA470300N0085520E470644N0085449E160160379386








































regulation system






tool








Filed Flight Plan

CDM

Header

Point Profile

Airspace Profile

Circle Intersection

Profile

RTFM Profile

CTFM Profile

CFP Profile

FTFM Profile






DATA TYPES




bull optimization

Aircraft

Performance

Data



High-lift device















High-lift device





DATA TYPES


ndash Cost Index



Business Rules

euro



A

B

C

DEP

DEP

DEP

21

25

23

A

A

E

B

52

40

CG 45

B

B

E

F

49

53

G

G

F

J

73

79

E

E

K

H

84

75

F

F

H

I

70

67

I

I

L

M

96

85

HL 86

JM 119

KO 117

KL 109

MQ 115

LP 118

QDEST 134

OP 136

PDEST 130

Worklist

Dijkstra algorithm

DEPDEST

16

40

19

12

19

J

28

34

I14

17

O33

25

Q30

P32

F24

28

D

E

19

31

G22

A

B

C

2125

23

H

K

35

26 L

M18

29







FL350

FL310

FL280

FL260

FL240

FL220

Maximum flightlevel

Optimum flightlevel



If


DIJKSTRAS ALGORITHM



Approach Greedy



























SID


SIDs and STARs



Wind forecast



calculation


runway to runway

STAR



Enroute alternate 1

Enroute alternate 3

Escape route

Flight direction

Terrain

Continuing point

No-Return point

Diversion area




Decision points




Enroute alternate 2




NP-complete problem









+ time allocation

V

L

T








HOW BIG DATA MINING





Ant-Colony

Branch amp Bound


Evolution Strategy

Dynamic Programming

Simulated Annealing

Tabu-Search

Particle Swarm

HOW TO USE BIG DATA



optimization






efficiency

Lower Airspace






euro

AOC



spaces


way through the AOC

accuracy space

NM ATC



wide



parameters

accuracy space





Needs




Airspace

User

ATC(Cost efficient)






INCIDENT ANALYSIS

INCIDENT ANALYSIS


72






77

PROOF OF MODEL

78


79

CHANGE MANAGEMENT

80


GAP ANALYSIS

82


DATA TYPES

bull Cost Index



Route Type amp

Optimization

Settings

COST DEFINITION

COST INDEX EXAMPLE


FIDL EXAMPLE

INPUTS







STARs and SIDs

bull ie ATFM policy


(APM)

bull Based on BADA



FIDL EXAMPLE



FIDL EXAMPLE



FIDL EXAMPLE



FIDL EXAMPLE


DATA TYPES

bull Flight Plan





Basic Flight

Data amp

Schedule









044840DCT160597V490001N0083550E76N 045435DCT75623V491355N0083323E88N












042020LSTSA40P042115ERSA470300N0085520E470644N0085449E160160379386








































regulation system






tool








Filed Flight Plan

CDM

Header

Point Profile

Airspace Profile

Circle Intersection

Profile

RTFM Profile

CTFM Profile

CFP Profile

FTFM Profile






DATA TYPES




bull optimization

Aircraft

Performance

Data



High-lift device















High-lift device





DATA TYPES


ndash Cost Index



Business Rules

euro



A

B

C

DEP

DEP

DEP

21

25

23

A

A

E

B

52

40

CG 45

B

B

E

F

49

53

G

G

F

J

73

79

E

E

K

H

84

75

F

F

H

I

70

67

I

I

L

M

96

85

HL 86

JM 119

KO 117

KL 109

MQ 115

LP 118

QDEST 134

OP 136

PDEST 130

Worklist

Dijkstra algorithm

DEPDEST

16

40

19

12

19

J

28

34

I14

17

O33

25

Q30

P32

F24

28

D

E

19

31

G22

A

B

C

2125

23

H

K

35

26 L

M18

29







FL350

FL310

FL280

FL260

FL240

FL220

Maximum flightlevel

Optimum flightlevel



If


DIJKSTRAS ALGORITHM



Approach Greedy



























SID


SIDs and STARs



Wind forecast



calculation


runway to runway

STAR



Enroute alternate 1

Enroute alternate 3

Escape route

Flight direction

Terrain

Continuing point

No-Return point

Diversion area




Decision points




Enroute alternate 2




NP-complete problem









+ time allocation

V

L

T








HOW BIG DATA MINING





Ant-Colony

Branch amp Bound


Evolution Strategy

Dynamic Programming

Simulated Annealing

Tabu-Search

Particle Swarm

HOW TO USE BIG DATA



optimization






efficiency

Lower Airspace






euro

AOC



spaces


way through the AOC

accuracy space

NM ATC



wide



parameters

accuracy space





Needs




Airspace

User

ATC(Cost efficient)






INCIDENT ANALYSIS

INCIDENT ANALYSIS


72






77

PROOF OF MODEL

78


79

CHANGE MANAGEMENT

80


GAP ANALYSIS

82


COST DEFINITION

COST INDEX EXAMPLE


FIDL EXAMPLE

INPUTS







STARs and SIDs

bull ie ATFM policy


(APM)

bull Based on BADA



FIDL EXAMPLE



FIDL EXAMPLE



FIDL EXAMPLE



FIDL EXAMPLE


DATA TYPES

bull Flight Plan





Basic Flight

Data amp

Schedule









044840DCT160597V490001N0083550E76N 045435DCT75623V491355N0083323E88N












042020LSTSA40P042115ERSA470300N0085520E470644N0085449E160160379386








































regulation system






tool








Filed Flight Plan

CDM

Header

Point Profile

Airspace Profile

Circle Intersection

Profile

RTFM Profile

CTFM Profile

CFP Profile

FTFM Profile






DATA TYPES




bull optimization

Aircraft

Performance

Data



High-lift device















High-lift device





DATA TYPES


ndash Cost Index



Business Rules

euro



A

B

C

DEP

DEP

DEP

21

25

23

A

A

E

B

52

40

CG 45

B

B

E

F

49

53

G

G

F

J

73

79

E

E

K

H

84

75

F

F

H

I

70

67

I

I

L

M

96

85

HL 86

JM 119

KO 117

KL 109

MQ 115

LP 118

QDEST 134

OP 136

PDEST 130

Worklist

Dijkstra algorithm

DEPDEST

16

40

19

12

19

J

28

34

I14

17

O33

25

Q30

P32

F24

28

D

E

19

31

G22

A

B

C

2125

23

H

K

35

26 L

M18

29







FL350

FL310

FL280

FL260

FL240

FL220

Maximum flightlevel

Optimum flightlevel



If


DIJKSTRAS ALGORITHM



Approach Greedy



























SID


SIDs and STARs



Wind forecast



calculation


runway to runway

STAR



Enroute alternate 1

Enroute alternate 3

Escape route

Flight direction

Terrain

Continuing point

No-Return point

Diversion area




Decision points




Enroute alternate 2




NP-complete problem









+ time allocation

V

L

T








HOW BIG DATA MINING





Ant-Colony

Branch amp Bound


Evolution Strategy

Dynamic Programming

Simulated Annealing

Tabu-Search

Particle Swarm

HOW TO USE BIG DATA



optimization






efficiency

Lower Airspace






euro

AOC



spaces


way through the AOC

accuracy space

NM ATC



wide



parameters

accuracy space





Needs




Airspace

User

ATC(Cost efficient)






INCIDENT ANALYSIS

INCIDENT ANALYSIS


72






77

PROOF OF MODEL

78


79

CHANGE MANAGEMENT

80


GAP ANALYSIS

82


COST INDEX EXAMPLE


FIDL EXAMPLE

INPUTS







STARs and SIDs

bull ie ATFM policy


(APM)

bull Based on BADA



FIDL EXAMPLE



FIDL EXAMPLE



FIDL EXAMPLE



FIDL EXAMPLE


DATA TYPES

bull Flight Plan





Basic Flight

Data amp

Schedule









044840DCT160597V490001N0083550E76N 045435DCT75623V491355N0083323E88N












042020LSTSA40P042115ERSA470300N0085520E470644N0085449E160160379386








































regulation system






tool








Filed Flight Plan

CDM

Header

Point Profile

Airspace Profile

Circle Intersection

Profile

RTFM Profile

CTFM Profile

CFP Profile

FTFM Profile






DATA TYPES




bull optimization

Aircraft

Performance

Data



High-lift device















High-lift device





DATA TYPES


ndash Cost Index



Business Rules

euro



A

B

C

DEP

DEP

DEP

21

25

23

A

A

E

B

52

40

CG 45

B

B

E

F

49

53

G

G

F

J

73

79

E

E

K

H

84

75

F

F

H

I

70

67

I

I

L

M

96

85

HL 86

JM 119

KO 117

KL 109

MQ 115

LP 118

QDEST 134

OP 136

PDEST 130

Worklist

Dijkstra algorithm

DEPDEST

16

40

19

12

19

J

28

34

I14

17

O33

25

Q30

P32

F24

28

D

E

19

31

G22

A

B

C

2125

23

H

K

35

26 L

M18

29







FL350

FL310

FL280

FL260

FL240

FL220

Maximum flightlevel

Optimum flightlevel



If


DIJKSTRAS ALGORITHM



Approach Greedy



























SID


SIDs and STARs



Wind forecast



calculation


runway to runway

STAR



Enroute alternate 1

Enroute alternate 3

Escape route

Flight direction

Terrain

Continuing point

No-Return point

Diversion area




Decision points




Enroute alternate 2




NP-complete problem









+ time allocation

V

L

T








HOW BIG DATA MINING





Ant-Colony

Branch amp Bound


Evolution Strategy

Dynamic Programming

Simulated Annealing

Tabu-Search

Particle Swarm

HOW TO USE BIG DATA



optimization






efficiency

Lower Airspace






euro

AOC



spaces


way through the AOC

accuracy space

NM ATC



wide



parameters

accuracy space





Needs




Airspace

User

ATC(Cost efficient)






INCIDENT ANALYSIS

INCIDENT ANALYSIS


72






77

PROOF OF MODEL

78


79

CHANGE MANAGEMENT

80


GAP ANALYSIS

82



FIDL EXAMPLE

INPUTS







STARs and SIDs

bull ie ATFM policy


(APM)

bull Based on BADA



FIDL EXAMPLE



FIDL EXAMPLE



FIDL EXAMPLE



FIDL EXAMPLE


DATA TYPES

bull Flight Plan





Basic Flight

Data amp

Schedule









044840DCT160597V490001N0083550E76N 045435DCT75623V491355N0083323E88N












042020LSTSA40P042115ERSA470300N0085520E470644N0085449E160160379386








































regulation system






tool








Filed Flight Plan

CDM

Header

Point Profile

Airspace Profile

Circle Intersection

Profile

RTFM Profile

CTFM Profile

CFP Profile

FTFM Profile






DATA TYPES




bull optimization

Aircraft

Performance

Data



High-lift device















High-lift device





DATA TYPES


ndash Cost Index



Business Rules

euro



A

B

C

DEP

DEP

DEP

21

25

23

A

A

E

B

52

40

CG 45

B

B

E

F

49

53

G

G

F

J

73

79

E

E

K

H

84

75

F

F

H

I

70

67

I

I

L

M

96

85

HL 86

JM 119

KO 117

KL 109

MQ 115

LP 118

QDEST 134

OP 136

PDEST 130

Worklist

Dijkstra algorithm

DEPDEST

16

40

19

12

19

J

28

34

I14

17

O33

25

Q30

P32

F24

28

D

E

19

31

G22

A

B

C

2125

23

H

K

35

26 L

M18

29







FL350

FL310

FL280

FL260

FL240

FL220

Maximum flightlevel

Optimum flightlevel



If


DIJKSTRAS ALGORITHM



Approach Greedy



























SID


SIDs and STARs



Wind forecast



calculation


runway to runway

STAR



Enroute alternate 1

Enroute alternate 3

Escape route

Flight direction

Terrain

Continuing point

No-Return point

Diversion area




Decision points




Enroute alternate 2




NP-complete problem









+ time allocation

V

L

T








HOW BIG DATA MINING





Ant-Colony

Branch amp Bound


Evolution Strategy

Dynamic Programming

Simulated Annealing

Tabu-Search

Particle Swarm

HOW TO USE BIG DATA



optimization






efficiency

Lower Airspace






euro

AOC



spaces


way through the AOC

accuracy space

NM ATC



wide



parameters

accuracy space





Needs




Airspace

User

ATC(Cost efficient)






INCIDENT ANALYSIS

INCIDENT ANALYSIS


72






77

PROOF OF MODEL

78


79

CHANGE MANAGEMENT

80


GAP ANALYSIS

82



FIDL EXAMPLE



FIDL EXAMPLE



FIDL EXAMPLE



FIDL EXAMPLE


DATA TYPES

bull Flight Plan





Basic Flight

Data amp

Schedule









044840DCT160597V490001N0083550E76N 045435DCT75623V491355N0083323E88N












042020LSTSA40P042115ERSA470300N0085520E470644N0085449E160160379386








































regulation system






tool








Filed Flight Plan

CDM

Header

Point Profile

Airspace Profile

Circle Intersection

Profile

RTFM Profile

CTFM Profile

CFP Profile

FTFM Profile






DATA TYPES




bull optimization

Aircraft

Performance

Data



High-lift device















High-lift device





DATA TYPES


ndash Cost Index



Business Rules

euro



A

B

C

DEP

DEP

DEP

21

25

23

A

A

E

B

52

40

CG 45

B

B

E

F

49

53

G

G

F

J

73

79

E

E

K

H

84

75

F

F

H

I

70

67

I

I

L

M

96

85

HL 86

JM 119

KO 117

KL 109

MQ 115

LP 118

QDEST 134

OP 136

PDEST 130

Worklist

Dijkstra algorithm

DEPDEST

16

40

19

12

19

J

28

34

I14

17

O33

25

Q30

P32

F24

28

D

E

19

31

G22

A

B

C

2125

23

H

K

35

26 L

M18

29







FL350

FL310

FL280

FL260

FL240

FL220

Maximum flightlevel

Optimum flightlevel



If


DIJKSTRAS ALGORITHM



Approach Greedy



























SID


SIDs and STARs



Wind forecast



calculation


runway to runway

STAR



Enroute alternate 1

Enroute alternate 3

Escape route

Flight direction

Terrain

Continuing point

No-Return point

Diversion area




Decision points




Enroute alternate 2




NP-complete problem









+ time allocation

V

L

T








HOW BIG DATA MINING





Ant-Colony

Branch amp Bound


Evolution Strategy

Dynamic Programming

Simulated Annealing

Tabu-Search

Particle Swarm

HOW TO USE BIG DATA



optimization






efficiency

Lower Airspace






euro

AOC



spaces


way through the AOC

accuracy space

NM ATC



wide



parameters

accuracy space





Needs




Airspace

User

ATC(Cost efficient)






INCIDENT ANALYSIS

INCIDENT ANALYSIS


72






77

PROOF OF MODEL

78


79

CHANGE MANAGEMENT

80


GAP ANALYSIS

82



FIDL EXAMPLE



FIDL EXAMPLE



FIDL EXAMPLE


DATA TYPES

bull Flight Plan





Basic Flight

Data amp

Schedule









044840DCT160597V490001N0083550E76N 045435DCT75623V491355N0083323E88N












042020LSTSA40P042115ERSA470300N0085520E470644N0085449E160160379386








































regulation system






tool








Filed Flight Plan

CDM

Header

Point Profile

Airspace Profile

Circle Intersection

Profile

RTFM Profile

CTFM Profile

CFP Profile

FTFM Profile






DATA TYPES




bull optimization

Aircraft

Performance

Data



High-lift device















High-lift device





DATA TYPES


ndash Cost Index



Business Rules

euro



A

B

C

DEP

DEP

DEP

21

25

23

A

A

E

B

52

40

CG 45

B

B

E

F

49

53

G

G

F

J

73

79

E

E

K

H

84

75

F

F

H

I

70

67

I

I

L

M

96

85

HL 86

JM 119

KO 117

KL 109

MQ 115

LP 118

QDEST 134

OP 136

PDEST 130

Worklist

Dijkstra algorithm

DEPDEST

16

40

19

12

19

J

28

34

I14

17

O33

25

Q30

P32

F24

28

D

E

19

31

G22

A

B

C

2125

23

H

K

35

26 L

M18

29







FL350

FL310

FL280

FL260

FL240

FL220

Maximum flightlevel

Optimum flightlevel



If


DIJKSTRAS ALGORITHM



Approach Greedy



























SID


SIDs and STARs



Wind forecast



calculation


runway to runway

STAR



Enroute alternate 1

Enroute alternate 3

Escape route

Flight direction

Terrain

Continuing point

No-Return point

Diversion area




Decision points




Enroute alternate 2




NP-complete problem









+ time allocation

V

L

T








HOW BIG DATA MINING





Ant-Colony

Branch amp Bound


Evolution Strategy

Dynamic Programming

Simulated Annealing

Tabu-Search

Particle Swarm

HOW TO USE BIG DATA



optimization






efficiency

Lower Airspace






euro

AOC



spaces


way through the AOC

accuracy space

NM ATC



wide



parameters

accuracy space





Needs




Airspace

User

ATC(Cost efficient)






INCIDENT ANALYSIS

INCIDENT ANALYSIS


72






77

PROOF OF MODEL

78


79

CHANGE MANAGEMENT

80


GAP ANALYSIS

82



FIDL EXAMPLE



FIDL EXAMPLE


DATA TYPES

bull Flight Plan





Basic Flight

Data amp

Schedule









044840DCT160597V490001N0083550E76N 045435DCT75623V491355N0083323E88N












042020LSTSA40P042115ERSA470300N0085520E470644N0085449E160160379386








































regulation system






tool








Filed Flight Plan

CDM

Header

Point Profile

Airspace Profile

Circle Intersection

Profile

RTFM Profile

CTFM Profile

CFP Profile

FTFM Profile






DATA TYPES




bull optimization

Aircraft

Performance

Data



High-lift device















High-lift device





DATA TYPES


ndash Cost Index



Business Rules

euro



A

B

C

DEP

DEP

DEP

21

25

23

A

A

E

B

52

40

CG 45

B

B

E

F

49

53

G

G

F

J

73

79

E

E

K

H

84

75

F

F

H

I

70

67

I

I

L

M

96

85

HL 86

JM 119

KO 117

KL 109

MQ 115

LP 118

QDEST 134

OP 136

PDEST 130

Worklist

Dijkstra algorithm

DEPDEST

16

40

19

12

19

J

28

34

I14

17

O33

25

Q30

P32

F24

28

D

E

19

31

G22

A

B

C

2125

23

H

K

35

26 L

M18

29







FL350

FL310

FL280

FL260

FL240

FL220

Maximum flightlevel

Optimum flightlevel



If


DIJKSTRAS ALGORITHM



Approach Greedy



























SID


SIDs and STARs



Wind forecast



calculation


runway to runway

STAR



Enroute alternate 1

Enroute alternate 3

Escape route

Flight direction

Terrain

Continuing point

No-Return point

Diversion area




Decision points




Enroute alternate 2




NP-complete problem









+ time allocation

V

L

T








HOW BIG DATA MINING





Ant-Colony

Branch amp Bound


Evolution Strategy

Dynamic Programming

Simulated Annealing

Tabu-Search

Particle Swarm

HOW TO USE BIG DATA



optimization






efficiency

Lower Airspace






euro

AOC



spaces


way through the AOC

accuracy space

NM ATC



wide



parameters

accuracy space





Needs




Airspace

User

ATC(Cost efficient)






INCIDENT ANALYSIS

INCIDENT ANALYSIS


72






77

PROOF OF MODEL

78


79

CHANGE MANAGEMENT

80


GAP ANALYSIS

82



FIDL EXAMPLE


DATA TYPES

bull Flight Plan





Basic Flight

Data amp

Schedule









044840DCT160597V490001N0083550E76N 045435DCT75623V491355N0083323E88N












042020LSTSA40P042115ERSA470300N0085520E470644N0085449E160160379386








































regulation system






tool








Filed Flight Plan

CDM

Header

Point Profile

Airspace Profile

Circle Intersection

Profile

RTFM Profile

CTFM Profile

CFP Profile

FTFM Profile






DATA TYPES




bull optimization

Aircraft

Performance

Data



High-lift device















High-lift device





DATA TYPES


ndash Cost Index



Business Rules

euro



A

B

C

DEP

DEP

DEP

21

25

23

A

A

E

B

52

40

CG 45

B

B

E

F

49

53

G

G

F

J

73

79

E

E

K

H

84

75

F

F

H

I

70

67

I

I

L

M

96

85

HL 86

JM 119

KO 117

KL 109

MQ 115

LP 118

QDEST 134

OP 136

PDEST 130

Worklist

Dijkstra algorithm

DEPDEST

16

40

19

12

19

J

28

34

I14

17

O33

25

Q30

P32

F24

28

D

E

19

31

G22

A

B

C

2125

23

H

K

35

26 L

M18

29







FL350

FL310

FL280

FL260

FL240

FL220

Maximum flightlevel

Optimum flightlevel



If


DIJKSTRAS ALGORITHM



Approach Greedy



























SID


SIDs and STARs



Wind forecast



calculation


runway to runway

STAR



Enroute alternate 1

Enroute alternate 3

Escape route

Flight direction

Terrain

Continuing point

No-Return point

Diversion area




Decision points




Enroute alternate 2




NP-complete problem









+ time allocation

V

L

T








HOW BIG DATA MINING





Ant-Colony

Branch amp Bound


Evolution Strategy

Dynamic Programming

Simulated Annealing

Tabu-Search

Particle Swarm

HOW TO USE BIG DATA



optimization






efficiency

Lower Airspace






euro

AOC



spaces


way through the AOC

accuracy space

NM ATC



wide



parameters

accuracy space





Needs




Airspace

User

ATC(Cost efficient)






INCIDENT ANALYSIS

INCIDENT ANALYSIS


72






77

PROOF OF MODEL

78


79

CHANGE MANAGEMENT

80


GAP ANALYSIS

82


DATA TYPES

bull Flight Plan





Basic Flight

Data amp

Schedule









044840DCT160597V490001N0083550E76N 045435DCT75623V491355N0083323E88N












042020LSTSA40P042115ERSA470300N0085520E470644N0085449E160160379386








































regulation system






tool








Filed Flight Plan

CDM

Header

Point Profile

Airspace Profile

Circle Intersection

Profile

RTFM Profile

CTFM Profile

CFP Profile

FTFM Profile






DATA TYPES




bull optimization

Aircraft

Performance

Data



High-lift device















High-lift device





DATA TYPES


ndash Cost Index



Business Rules

euro



A

B

C

DEP

DEP

DEP

21

25

23

A

A

E

B

52

40

CG 45

B

B

E

F

49

53

G

G

F

J

73

79

E

E

K

H

84

75

F

F

H

I

70

67

I

I

L

M

96

85

HL 86

JM 119

KO 117

KL 109

MQ 115

LP 118

QDEST 134

OP 136

PDEST 130

Worklist

Dijkstra algorithm

DEPDEST

16

40

19

12

19

J

28

34

I14

17

O33

25

Q30

P32

F24

28

D

E

19

31

G22

A

B

C

2125

23

H

K

35

26 L

M18

29







FL350

FL310

FL280

FL260

FL240

FL220

Maximum flightlevel

Optimum flightlevel



If


DIJKSTRAS ALGORITHM



Approach Greedy



























SID


SIDs and STARs



Wind forecast



calculation


runway to runway

STAR



Enroute alternate 1

Enroute alternate 3

Escape route

Flight direction

Terrain

Continuing point

No-Return point

Diversion area




Decision points




Enroute alternate 2




NP-complete problem









+ time allocation

V

L

T








HOW BIG DATA MINING





Ant-Colony

Branch amp Bound


Evolution Strategy

Dynamic Programming

Simulated Annealing

Tabu-Search

Particle Swarm

HOW TO USE BIG DATA



optimization






efficiency

Lower Airspace






euro

AOC



spaces


way through the AOC

accuracy space

NM ATC



wide



parameters

accuracy space





Needs




Airspace

User

ATC(Cost efficient)






INCIDENT ANALYSIS

INCIDENT ANALYSIS


72






77

PROOF OF MODEL

78


79

CHANGE MANAGEMENT

80


GAP ANALYSIS

82










044840DCT160597V490001N0083550E76N 045435DCT75623V491355N0083323E88N












042020LSTSA40P042115ERSA470300N0085520E470644N0085449E160160379386








































regulation system






tool








Filed Flight Plan

CDM

Header

Point Profile

Airspace Profile

Circle Intersection

Profile

RTFM Profile

CTFM Profile

CFP Profile

FTFM Profile






DATA TYPES




bull optimization

Aircraft

Performance

Data



High-lift device















High-lift device





DATA TYPES


ndash Cost Index



Business Rules

euro



A

B

C

DEP

DEP

DEP

21

25

23

A

A

E

B

52

40

CG 45

B

B

E

F

49

53

G

G

F

J

73

79

E

E

K

H

84

75

F

F

H

I

70

67

I

I

L

M

96

85

HL 86

JM 119

KO 117

KL 109

MQ 115

LP 118

QDEST 134

OP 136

PDEST 130

Worklist

Dijkstra algorithm

DEPDEST

16

40

19

12

19

J

28

34

I14

17

O33

25

Q30

P32

F24

28

D

E

19

31

G22

A

B

C

2125

23

H

K

35

26 L

M18

29







FL350

FL310

FL280

FL260

FL240

FL220

Maximum flightlevel

Optimum flightlevel



If


DIJKSTRAS ALGORITHM



Approach Greedy



























SID


SIDs and STARs



Wind forecast



calculation


runway to runway

STAR



Enroute alternate 1

Enroute alternate 3

Escape route

Flight direction

Terrain

Continuing point

No-Return point

Diversion area




Decision points




Enroute alternate 2




NP-complete problem









+ time allocation

V

L

T








HOW BIG DATA MINING





Ant-Colony

Branch amp Bound


Evolution Strategy

Dynamic Programming

Simulated Annealing

Tabu-Search

Particle Swarm

HOW TO USE BIG DATA



optimization






efficiency

Lower Airspace






euro

AOC



spaces


way through the AOC

accuracy space

NM ATC



wide



parameters

accuracy space





Needs




Airspace

User

ATC(Cost efficient)






INCIDENT ANALYSIS

INCIDENT ANALYSIS


72






77

PROOF OF MODEL

78


79

CHANGE MANAGEMENT

80


GAP ANALYSIS

82












regulation system






tool








Filed Flight Plan

CDM

Header

Point Profile

Airspace Profile

Circle Intersection

Profile

RTFM Profile

CTFM Profile

CFP Profile

FTFM Profile






DATA TYPES




bull optimization

Aircraft

Performance

Data



High-lift device















High-lift device





DATA TYPES


ndash Cost Index



Business Rules

euro



A

B

C

DEP

DEP

DEP

21

25

23

A

A

E

B

52

40

CG 45

B

B

E

F

49

53

G

G

F

J

73

79

E

E

K

H

84

75

F

F

H

I

70

67

I

I

L

M

96

85

HL 86

JM 119

KO 117

KL 109

MQ 115

LP 118

QDEST 134

OP 136

PDEST 130

Worklist

Dijkstra algorithm

DEPDEST

16

40

19

12

19

J

28

34

I14

17

O33

25

Q30

P32

F24

28

D

E

19

31

G22

A

B

C

2125

23

H

K

35

26 L

M18

29







FL350

FL310

FL280

FL260

FL240

FL220

Maximum flightlevel

Optimum flightlevel



If


DIJKSTRAS ALGORITHM



Approach Greedy



























SID


SIDs and STARs



Wind forecast



calculation


runway to runway

STAR



Enroute alternate 1

Enroute alternate 3

Escape route

Flight direction

Terrain

Continuing point

No-Return point

Diversion area




Decision points




Enroute alternate 2




NP-complete problem









+ time allocation

V

L

T








HOW BIG DATA MINING





Ant-Colony

Branch amp Bound


Evolution Strategy

Dynamic Programming

Simulated Annealing

Tabu-Search

Particle Swarm

HOW TO USE BIG DATA



optimization






efficiency

Lower Airspace






euro

AOC



spaces


way through the AOC

accuracy space

NM ATC



wide



parameters

accuracy space





Needs




Airspace

User

ATC(Cost efficient)






INCIDENT ANALYSIS

INCIDENT ANALYSIS


72






77

PROOF OF MODEL

78


79

CHANGE MANAGEMENT

80


GAP ANALYSIS

82







DATA TYPES




bull optimization

Aircraft

Performance

Data



High-lift device















High-lift device





DATA TYPES


ndash Cost Index



Business Rules

euro



A

B

C

DEP

DEP

DEP

21

25

23

A

A

E

B

52

40

CG 45

B

B

E

F

49

53

G

G

F

J

73

79

E

E

K

H

84

75

F

F

H

I

70

67

I

I

L

M

96

85

HL 86

JM 119

KO 117

KL 109

MQ 115

LP 118

QDEST 134

OP 136

PDEST 130

Worklist

Dijkstra algorithm

DEPDEST

16

40

19

12

19

J

28

34

I14

17

O33

25

Q30

P32

F24

28

D

E

19

31

G22

A

B

C

2125

23

H

K

35

26 L

M18

29







FL350

FL310

FL280

FL260

FL240

FL220

Maximum flightlevel

Optimum flightlevel



If


DIJKSTRAS ALGORITHM



Approach Greedy



























SID


SIDs and STARs



Wind forecast



calculation


runway to runway

STAR



Enroute alternate 1

Enroute alternate 3

Escape route

Flight direction

Terrain

Continuing point

No-Return point

Diversion area




Decision points




Enroute alternate 2




NP-complete problem









+ time allocation

V

L

T








HOW BIG DATA MINING





Ant-Colony

Branch amp Bound


Evolution Strategy

Dynamic Programming

Simulated Annealing

Tabu-Search

Particle Swarm

HOW TO USE BIG DATA



optimization






efficiency

Lower Airspace






euro

AOC



spaces


way through the AOC

accuracy space

NM ATC



wide



parameters

accuracy space





Needs




Airspace

User

ATC(Cost efficient)






INCIDENT ANALYSIS

INCIDENT ANALYSIS


72






77

PROOF OF MODEL

78


79

CHANGE MANAGEMENT

80


GAP ANALYSIS

82




High-lift device















High-lift device





DATA TYPES


ndash Cost Index



Business Rules

euro



A

B

C

DEP

DEP

DEP

21

25

23

A

A

E

B

52

40

CG 45

B

B

E

F

49

53

G

G

F

J

73

79

E

E

K

H

84

75

F

F

H

I

70

67

I

I

L

M

96

85

HL 86

JM 119

KO 117

KL 109

MQ 115

LP 118

QDEST 134

OP 136

PDEST 130

Worklist

Dijkstra algorithm

DEPDEST

16

40

19

12

19

J

28

34

I14

17

O33

25

Q30

P32

F24

28

D

E

19

31

G22

A

B

C

2125

23

H

K

35

26 L

M18

29







FL350

FL310

FL280

FL260

FL240

FL220

Maximum flightlevel

Optimum flightlevel



If


DIJKSTRAS ALGORITHM



Approach Greedy



























SID


SIDs and STARs



Wind forecast



calculation


runway to runway

STAR



Enroute alternate 1

Enroute alternate 3

Escape route

Flight direction

Terrain

Continuing point

No-Return point

Diversion area




Decision points




Enroute alternate 2




NP-complete problem









+ time allocation

V

L

T








HOW BIG DATA MINING





Ant-Colony

Branch amp Bound


Evolution Strategy

Dynamic Programming

Simulated Annealing

Tabu-Search

Particle Swarm

HOW TO USE BIG DATA



optimization






efficiency

Lower Airspace






euro

AOC



spaces


way through the AOC

accuracy space

NM ATC



wide



parameters

accuracy space





Needs




Airspace

User

ATC(Cost efficient)






INCIDENT ANALYSIS

INCIDENT ANALYSIS


72






77

PROOF OF MODEL

78


79

CHANGE MANAGEMENT

80


GAP ANALYSIS

82












High-lift device





DATA TYPES


ndash Cost Index



Business Rules

euro



A

B

C

DEP

DEP

DEP

21

25

23

A

A

E

B

52

40

CG 45

B

B

E

F

49

53

G

G

F

J

73

79

E

E

K

H

84

75

F

F

H

I

70

67

I

I

L

M

96

85

HL 86

JM 119

KO 117

KL 109

MQ 115

LP 118

QDEST 134

OP 136

PDEST 130

Worklist

Dijkstra algorithm

DEPDEST

16

40

19

12

19

J

28

34

I14

17

O33

25

Q30

P32

F24

28

D

E

19

31

G22

A

B

C

2125

23

H

K

35

26 L

M18

29







FL350

FL310

FL280

FL260

FL240

FL220

Maximum flightlevel

Optimum flightlevel



If


DIJKSTRAS ALGORITHM



Approach Greedy



























SID


SIDs and STARs



Wind forecast



calculation


runway to runway

STAR



Enroute alternate 1

Enroute alternate 3

Escape route

Flight direction

Terrain

Continuing point

No-Return point

Diversion area




Decision points




Enroute alternate 2




NP-complete problem









+ time allocation

V

L

T








HOW BIG DATA MINING





Ant-Colony

Branch amp Bound


Evolution Strategy

Dynamic Programming

Simulated Annealing

Tabu-Search

Particle Swarm

HOW TO USE BIG DATA



optimization






efficiency

Lower Airspace






euro

AOC



spaces


way through the AOC

accuracy space

NM ATC



wide



parameters

accuracy space





Needs




Airspace

User

ATC(Cost efficient)






INCIDENT ANALYSIS

INCIDENT ANALYSIS


72






77

PROOF OF MODEL

78


79

CHANGE MANAGEMENT

80


GAP ANALYSIS

82



DATA TYPES


ndash Cost Index



Business Rules

euro



A

B

C

DEP

DEP

DEP

21

25

23

A

A

E

B

52

40

CG 45

B

B

E

F

49

53

G

G

F

J

73

79

E

E

K

H

84

75

F

F

H

I

70

67

I

I

L

M

96

85

HL 86

JM 119

KO 117

KL 109

MQ 115

LP 118

QDEST 134

OP 136

PDEST 130

Worklist

Dijkstra algorithm

DEPDEST

16

40

19

12

19

J

28

34

I14

17

O33

25

Q30

P32

F24

28

D

E

19

31

G22

A

B

C

2125

23

H

K

35

26 L

M18

29







FL350

FL310

FL280

FL260

FL240

FL220

Maximum flightlevel

Optimum flightlevel



If


DIJKSTRAS ALGORITHM



Approach Greedy



























SID


SIDs and STARs



Wind forecast



calculation


runway to runway

STAR



Enroute alternate 1

Enroute alternate 3

Escape route

Flight direction

Terrain

Continuing point

No-Return point

Diversion area




Decision points




Enroute alternate 2




NP-complete problem









+ time allocation

V

L

T








HOW BIG DATA MINING





Ant-Colony

Branch amp Bound


Evolution Strategy

Dynamic Programming

Simulated Annealing

Tabu-Search

Particle Swarm

HOW TO USE BIG DATA



optimization






efficiency

Lower Airspace






euro

AOC



spaces


way through the AOC

accuracy space

NM ATC



wide



parameters

accuracy space





Needs




Airspace

User

ATC(Cost efficient)






INCIDENT ANALYSIS

INCIDENT ANALYSIS


72






77

PROOF OF MODEL

78


79

CHANGE MANAGEMENT

80


GAP ANALYSIS

82




A

B

C

DEP

DEP

DEP

21

25

23

A

A

E

B

52

40

CG 45

B

B

E

F

49

53

G

G

F

J

73

79

E

E

K

H

84

75

F

F

H

I

70

67

I

I

L

M

96

85

HL 86

JM 119

KO 117

KL 109

MQ 115

LP 118

QDEST 134

OP 136

PDEST 130

Worklist

Dijkstra algorithm

DEPDEST

16

40

19

12

19

J

28

34

I14

17

O33

25

Q30

P32

F24

28

D

E

19

31

G22

A

B

C

2125

23

H

K

35

26 L

M18

29







FL350

FL310

FL280

FL260

FL240

FL220

Maximum flightlevel

Optimum flightlevel



If


DIJKSTRAS ALGORITHM



Approach Greedy



























SID


SIDs and STARs



Wind forecast



calculation


runway to runway

STAR



Enroute alternate 1

Enroute alternate 3

Escape route

Flight direction

Terrain

Continuing point

No-Return point

Diversion area




Decision points




Enroute alternate 2




NP-complete problem









+ time allocation

V

L

T








HOW BIG DATA MINING





Ant-Colony

Branch amp Bound


Evolution Strategy

Dynamic Programming

Simulated Annealing

Tabu-Search

Particle Swarm

HOW TO USE BIG DATA



optimization






efficiency

Lower Airspace






euro

AOC



spaces


way through the AOC

accuracy space

NM ATC



wide



parameters

accuracy space





Needs




Airspace

User

ATC(Cost efficient)






INCIDENT ANALYSIS

INCIDENT ANALYSIS


72






77

PROOF OF MODEL

78


79

CHANGE MANAGEMENT

80


GAP ANALYSIS

82



FL350

FL310

FL280

FL260

FL240

FL220

Maximum flightlevel

Optimum flightlevel



If


DIJKSTRAS ALGORITHM



Approach Greedy



























SID


SIDs and STARs



Wind forecast



calculation


runway to runway

STAR



Enroute alternate 1

Enroute alternate 3

Escape route

Flight direction

Terrain

Continuing point

No-Return point

Diversion area




Decision points




Enroute alternate 2




NP-complete problem









+ time allocation

V

L

T








HOW BIG DATA MINING





Ant-Colony

Branch amp Bound


Evolution Strategy

Dynamic Programming

Simulated Annealing

Tabu-Search

Particle Swarm

HOW TO USE BIG DATA



optimization






efficiency

Lower Airspace






euro

AOC



spaces


way through the AOC

accuracy space

NM ATC



wide



parameters

accuracy space





Needs




Airspace

User

ATC(Cost efficient)






INCIDENT ANALYSIS

INCIDENT ANALYSIS


72






77

PROOF OF MODEL

78


79

CHANGE MANAGEMENT

80


GAP ANALYSIS

82


DIJKSTRAS ALGORITHM



Approach Greedy



























SID


SIDs and STARs



Wind forecast



calculation


runway to runway

STAR



Enroute alternate 1

Enroute alternate 3

Escape route

Flight direction

Terrain

Continuing point

No-Return point

Diversion area




Decision points




Enroute alternate 2




NP-complete problem









+ time allocation

V

L

T








HOW BIG DATA MINING





Ant-Colony

Branch amp Bound


Evolution Strategy

Dynamic Programming

Simulated Annealing

Tabu-Search

Particle Swarm

HOW TO USE BIG DATA



optimization






efficiency

Lower Airspace






euro

AOC



spaces


way through the AOC

accuracy space

NM ATC



wide



parameters

accuracy space





Needs




Airspace

User

ATC(Cost efficient)






INCIDENT ANALYSIS

INCIDENT ANALYSIS


72






77

PROOF OF MODEL

78


79

CHANGE MANAGEMENT

80


GAP ANALYSIS

82


























SID


SIDs and STARs



Wind forecast



calculation


runway to runway

STAR



Enroute alternate 1

Enroute alternate 3

Escape route

Flight direction

Terrain

Continuing point

No-Return point

Diversion area




Decision points




Enroute alternate 2




NP-complete problem









+ time allocation

V

L

T








HOW BIG DATA MINING





Ant-Colony

Branch amp Bound


Evolution Strategy

Dynamic Programming

Simulated Annealing

Tabu-Search

Particle Swarm

HOW TO USE BIG DATA



optimization






efficiency

Lower Airspace






euro

AOC



spaces


way through the AOC

accuracy space

NM ATC



wide



parameters

accuracy space





Needs




Airspace

User

ATC(Cost efficient)






INCIDENT ANALYSIS

INCIDENT ANALYSIS


72






77

PROOF OF MODEL

78


79

CHANGE MANAGEMENT

80


GAP ANALYSIS

82




Enroute alternate 1

Enroute alternate 3

Escape route

Flight direction

Terrain

Continuing point

No-Return point

Diversion area




Decision points




Enroute alternate 2




NP-complete problem









+ time allocation

V

L

T








HOW BIG DATA MINING





Ant-Colony

Branch amp Bound


Evolution Strategy

Dynamic Programming

Simulated Annealing

Tabu-Search

Particle Swarm

HOW TO USE BIG DATA



optimization






efficiency

Lower Airspace






euro

AOC



spaces


way through the AOC

accuracy space

NM ATC



wide



parameters

accuracy space





Needs




Airspace

User

ATC(Cost efficient)






INCIDENT ANALYSIS

INCIDENT ANALYSIS


72






77

PROOF OF MODEL

78


79

CHANGE MANAGEMENT

80


GAP ANALYSIS

82





NP-complete problem









+ time allocation

V

L

T








HOW BIG DATA MINING





Ant-Colony

Branch amp Bound


Evolution Strategy

Dynamic Programming

Simulated Annealing

Tabu-Search

Particle Swarm

HOW TO USE BIG DATA



optimization






efficiency

Lower Airspace






euro

AOC



spaces


way through the AOC

accuracy space

NM ATC



wide



parameters

accuracy space





Needs




Airspace

User

ATC(Cost efficient)






INCIDENT ANALYSIS

INCIDENT ANALYSIS


72






77

PROOF OF MODEL

78


79

CHANGE MANAGEMENT

80


GAP ANALYSIS

82




+ time allocation

V

L

T








HOW BIG DATA MINING





Ant-Colony

Branch amp Bound


Evolution Strategy

Dynamic Programming

Simulated Annealing

Tabu-Search

Particle Swarm

HOW TO USE BIG DATA



optimization






efficiency

Lower Airspace






euro

AOC



spaces


way through the AOC

accuracy space

NM ATC



wide



parameters

accuracy space





Needs




Airspace

User

ATC(Cost efficient)






INCIDENT ANALYSIS

INCIDENT ANALYSIS


72






77

PROOF OF MODEL

78


79

CHANGE MANAGEMENT

80


GAP ANALYSIS

82









HOW BIG DATA MINING





Ant-Colony

Branch amp Bound


Evolution Strategy

Dynamic Programming

Simulated Annealing

Tabu-Search

Particle Swarm

HOW TO USE BIG DATA



optimization






efficiency

Lower Airspace






euro

AOC



spaces


way through the AOC

accuracy space

NM ATC



wide



parameters

accuracy space





Needs




Airspace

User

ATC(Cost efficient)






INCIDENT ANALYSIS

INCIDENT ANALYSIS


72






77

PROOF OF MODEL

78


79

CHANGE MANAGEMENT

80


GAP ANALYSIS

82


HOW TO USE BIG DATA



optimization






efficiency

Lower Airspace






euro

AOC



spaces


way through the AOC

accuracy space

NM ATC



wide



parameters

accuracy space





Needs




Airspace

User

ATC(Cost efficient)






INCIDENT ANALYSIS

INCIDENT ANALYSIS


72






77

PROOF OF MODEL

78


79

CHANGE MANAGEMENT

80


GAP ANALYSIS

82


Lower Airspace






euro

AOC



spaces


way through the AOC

accuracy space

NM ATC



wide



parameters

accuracy space





Needs




Airspace

User

ATC(Cost efficient)






INCIDENT ANALYSIS

INCIDENT ANALYSIS


72






77

PROOF OF MODEL

78


79

CHANGE MANAGEMENT

80


GAP ANALYSIS

82






euro

AOC



spaces


way through the AOC

accuracy space

NM ATC



wide



parameters

accuracy space





Needs




Airspace

User

ATC(Cost efficient)






INCIDENT ANALYSIS

INCIDENT ANALYSIS


72






77

PROOF OF MODEL

78


79

CHANGE MANAGEMENT

80


GAP ANALYSIS

82






Needs




Airspace

User

ATC(Cost efficient)






INCIDENT ANALYSIS

INCIDENT ANALYSIS


72






77

PROOF OF MODEL

78


79

CHANGE MANAGEMENT

80


GAP ANALYSIS

82





INCIDENT ANALYSIS

INCIDENT ANALYSIS


72






77

PROOF OF MODEL

78


79

CHANGE MANAGEMENT

80


GAP ANALYSIS

82


INCIDENT ANALYSIS


72






77

PROOF OF MODEL

78


79

CHANGE MANAGEMENT

80


GAP ANALYSIS

82



72






77

PROOF OF MODEL

78


79

CHANGE MANAGEMENT

80


GAP ANALYSIS

82







77

PROOF OF MODEL

78


79

CHANGE MANAGEMENT

80


GAP ANALYSIS

82


PROOF OF MODEL

78


79

CHANGE MANAGEMENT

80


GAP ANALYSIS

82



79

CHANGE MANAGEMENT

80


GAP ANALYSIS

82


CHANGE MANAGEMENT

80


GAP ANALYSIS

82



GAP ANALYSIS

82


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