Durville _R_2013.pdf

Romain Durville

Applicability of the Initial 4D Trajectory Management Function to

Mixed Equipage Operations within the Near Future Single European

Sky

SCHOOL OF ENGINEERING

MSc Air Transport Management

MSc THESIS

Academic Year: 2012 - 2013

Supervisor: Andy Foster

August 2013

i

SCHOOL OF ENGINEERING

MSc Air Transport Management

MSc THESIS

Academic Year: 2012 - 2013

Romain Durville

Applicability of the Initial 4D Trajectory Management Function to

Mixed Equipage Operations within the Near Future Single European

Sky

Supervisor: Andy Foster

August 2013

This thesis is submitted in partial fulfilment of the requirements for

the degree of Master of Science

© Cranfield University 2013. All rights reserved. No part of this

publication may be reproduced without the written permission of the

copyright owner.

ii

Intentionally left blank

iii

ABSTRACT

In the recent evolutionary framework of the Air Traffic Management (ATM) in

Europe, with the Single European Sky ATM Research (SESAR) Programme,

significant challenges are starting to emerge in preparation for the deployment

phase of the programme. One of the greatest challenges is now to prepare and

ensure a synchronised deployment of each new future ATM concept or

innovation in a mixed equipage environment (i.e. a mix of equipped and

unequipped aircraft). Among the different related ATM concepts, the initial 4D

(i4D) Trajectory Management concept is especially mature, and will be

deployed shortly throughout the European sky. This ATM concept, defined and

supported by the SESAR Programme, is indeed one of the key steps of the

European ATM target concept for 2020 onwards. The purpose of this concept is

to cope with the growth in worldwide traffic and the continuous increase in

environmental constraints.

The research study hereinafter focuses on the assessment of the i4D Trajectory

Management concept for mixed equipage operations, within its deployment

timeline. The main objective was firstly to analyse if i4D operations in a mixed

equipage environment would bring benefits to i4D-equipped flights without

penalizing unequipped flights during the i4D deployment phase. In addition,

another study was carried out, in order to elucidate the degree of impact on the

deployment of i4D operations from both a global point of view and from an

airline’s perspective.

It has therefore been demonstrated that i4D operations in mixed equipage

operations will globally increase benefits throughout the deployment phase

compared to the situation today. While equipped flights will obtain significant

benefits during the entire deployment phase, unequipped flights will also obtain

benefits as soon as i4D operations become largely deployed. Finally, the last

conducted analysis revealed that specific precautions must be taken and that

the degree of benefits stemming from i4D operations will be significant for

airlines according to both their type of operations and their fleet age breakdown.

Keywords: ATM, SESAR, Deployment, i4D Operations, Equipped and

Unequipped Aircraft, Benefits

v

ACKNOWLEDGEMENTS

The completion of this research thesis is a milestone in seven years of intense

studies, during which I have had the opportunity to develop both my

interpersonal and professional skills. This final year at Cranfield University has

been an outstanding part of my student life during which I gained extensive

knowledge in the most stimulating academic environment I have known.

However, I would have never succeeded in joining Cranfield and achieving this

final Master thesis without the help and support of the people who surrounded

me.

First of all, I would like to sincerely thank my parents without whom I would have

never reached this level of education. They have always been there to

encourage me when I was in low spirits. In addition, special thanks go to the

rest of my family and to my closest friends who have always supported me in

my endeavours.

As regards this final three-month period, I would like to express my personal

gratitude to the following people:

Andy Foster, my thesis supervisor from Cranfield University, who has

supported me and advised me throughout the entire thesis period.

Benoît Couturier, my supervisor in Airbus with whom I carefully defined

my thesis subject. Benoît has been extremely helpful, providing me with

his continuous support, in addition to sharing his valuable knowledge and

opinions with me, every time I needed to enhance my research.

Other Airbus-related ATM experts who took the time to discuss with me

and to answer my questions, in particular Maud Rotureau, Daniel Ferro,

and Patrick Lelievre.

Finally, I am deeply grateful to Vérane who has been a constant comfort

throughout this intense academic year.

vi

Disclaimer Statement

This thesis has benefited from, and been aided by, the support, expert guidance

and data or information provision of organizations and/or persons

acknowledged herein. However, unless otherwise stated, no endorsement of

the results or methods employed in this research has been given by those

acknowledged, nor should such endorsement be assumed by the reader.

vii

TABLE OF CONTENTS

ABSTRACT ........................................................................................................ iii

ACKNOWLEDGEMENTS................................................................................... v

LIST OF FIGURES ............................................................................................. x

LIST OF TABLES .............................................................................................. xii

LIST OF ABBREVIATIONS .............................................................................. xiii

1 INTRODUCTION ............................................................................................. 1

1.1 Setting the Scene...................................................................................... 1

1.1.1 A Brief Introduction to the European ATM .......................................... 1

1.1.2 The Recent European ATM Reform ................................................... 3

1.2 Research Context ..................................................................................... 5

1.3 Research Limitations and Hypothesis ....................................................... 6

1.4 Research Aim and Specific Objectives ..................................................... 6

1.5 Structure of the Thesis .............................................................................. 7

2 LITERATURE REVIEW................................................................................... 9

2.1 An Overview of SESAR within the SES Context ....................................... 9

2.1.1 SES Performance Context ............................................................... 12

2.1.2 SESAR Programme vs. SESAR Joint Undertaking .......................... 13

2.1.3 SESAR Work Structure and Relationship with the Thesis Work ...... 16

2.1.4 SESAR Phases and Concept Steps ................................................. 18

2.1.5 Airbus within SESAR ........................................................................ 20

2.2 A Complete Overview of the i4D Function .............................................. 22

2.2.1 Primary Projects Achieved ............................................................... 22

2.2.2 I4D Trajectory Management Function Definition .............................. 24

2.2.3 I4D Operational Concept Description vs. Today Operations ............ 25

2.2.4 I4D Validation Steps through Flight Trials and Simulations .............. 33

2.2.5 Overall Benefit obtained from i4D Operations .................................. 35

2.3 Mixed Equipage ...................................................................................... 37

2.3.1 Overall Principle and i4D-Related Aircraft Equipage ........................ 37

2.3.2 Previous General Theoretical Studies .............................................. 39

viii

3 METHODOLOGY .......................................................................................... 41

3.1 Overall Thought Process ........................................................................ 41

3.2 Scope of the Study: Assumptions and Limitations .................................. 43

3.3 Experiment Design in Mixed Fleet Operations ........................................ 45

3.3.1 Deployment Phases/Flights Models Definition ................................. 47

3.3.2 Source: Compiled by the authorToday Base Model Considered

for Comparison .......................................................................................... 49

3.4 Identification of Key Enablers/Bottlenecks .............................................. 54

3.5 Case-Study Scenario Definition .............................................................. 56

4 RESULTS OF THE ANALYSIS AND DISCUSSION .................................... 59

4.1 Impact Assessment................................................................................. 59

4.1.1 Scenario 1 ........................................................................................ 60

4.1.2 Scenario 2 ........................................................................................ 62

4.1.3 Scenario 3 ........................................................................................ 64

4.1.4 Degree of Change during the i4D Deployment ................................. 66

4.2 Opportunities and Risk Assessment ....................................................... 70

4.2.1 Status for Equipped Flights .............................................................. 70

4.2.2 Status for Unequipped Flights .......................................................... 71

4.2.3 Overall Risk Assessment and Trails of Further Study ...................... 72

4.3 Implications and Impact on the i4D Implementation from an Airline’s

Perspective ................................................................................................... 73

4.3.1 Scope of the in-depth Fleet Analysis of EU Airlines ......................... 73

4.3.2 Results for Traditional Scheduled Airlines ........................................ 75

4.3.3 Results for Low Cost Airlines ........................................................... 77

4.3.4 Ways to Foster the Initial i4D Deployment – Strategic Principles ..... 79

4.4 Further Discussion on Final Results – Sensitivity Analysis ..................... 80

4.4.1 Regarding Degree of Change throughout the i4D Deployment ........ 80

4.4.2 Regarding the Fleet Analysis of EU Airlines ..................................... 81

5 CONCLUSION AND FUTURE WORK .......................................................... 83

5.1 Outcome of the Thesis and Conclusion on i4D Operations in a Mixed

Equipage Environment.................................................................................. 83

5.2 Recommendations and Next Steps ........................................................ 85

ix

REFERENCES ................................................................................................. 89

APPENDICES .................................................................................................. 95

x

LIST OF FIGURES

Figure 1-1 European ATM Global Structure ....................................................... 1

Figure 1-2 EU Performance Scheme - ATM Master Plan Goals ........................ 3

Figure 2-1 SESAR Programme – Overall Work Breakdown Structure ............. 17

Figure 2-2 SESAR Concept Steps and their Relationship to the Deployment

Baseline ..................................................................................................... 19

Figure 2-3 Different Steps of Air/Ground Exchanges throughout the Entire i4D

Operational Concept .................................................................................. 31

Figure 2-4 Route Flown during the First i4D Flight Trial ................................... 33

Figure 3-1 Overall Thought Process ................................................................. 41

Figure 3-2 44 Member Countries of the ECAC ................................................. 43

Figure 3-3 Considered Operational Area – AMAN Horizon .............................. 44

Figure 3-4 Considered Referential Flow of Today’s Arrival Sequencing .......... 44

Figure 3-5 Fleet Evolution Forecast from 2018 to 2030 related to the i4D

Deployment ............................................................................................... 47

Figure 3-6 Average Breakdown of Arrival Delay Causes at the Top 10 EU

Arrival Airports with Heaviest Delays in 2012 ............................................ 51

Figure 3-7 Today’s Base Model Considered for Comparison ........................... 52

Figure 3-8 Validation Targets Allocated to i4D ................................................. 54

Figure 4-1 Scenario 1 Assessment Matrix - Equipped vs. Unequipped Flights 60

Figure 4-2 Scenario 1 Assessment Matrix - Globally ........................................ 61



xi



Figure 4-7 Expected Degree of Change during the i4D Deployment –

Equipped Flights ........................................................................................ 67


Unequipped Flights .................................................................................... 68


Globally ...................................................................................................... 69

Figure 4-10 Market Share by Aviation Segments in Europe in 2012 ................ 73

Figure 4-11 Market Segmentation vs. Fleet Age for Traditional Scheduled

Airlines – Expected to end 2018 ................................................................ 75

Figure 4-12 Market Segmentation vs. Fleet Age for Low Cost Airlines –

Expected to end 2018 ................................................................................ 77

xii

LIST OF TABLES

Table 2-1 Main Differences between SESAR and NextGen ............................. 10

Table 2-2 Main Similarities between SESAR and NextGen ............................. 11

Table 2-3 Key Conceptual Differences in Operating Methods between Today’s

Operations and i4D Operations ................................................................. 32

Table 3-1 Defined i4D Deployment Phases ..................................................... 49

Table 3-2 Defined Flights Models ..................................................................... 49

Table 3-3 Breakdown of Actual All-Causes Arrival Punctuality in 2012 ............ 50

Table 4-1 Opportunities and Risk Assessment – Equipped Flights .................. 70

Table 4-2 Opportunities and Risk Assessment – Unequipped Flights .............. 71

Table 4-3 Assessment Matrix of Selected Traditional Scheduled Airlines –

Results for Expected Status in 2018 .......................................................... 76

Table 4-4 Assessment Matrix of Selected Low Cost Airlines – Results for

Expected Status in 2018 ............................................................................ 78

xiii

LIST OF ABBREVIATIONS

A/C

ADS-C

AMAN

ANS

ANSP

APP

ASAS

ATC

ATCO

ATFM

ATM

ATSU

CASE

CASSIS

CDA

CNS

CODA

CPDLC

CTA

DoC

DOC

ECAC

Aircraft

Automatic Dependant Surveillance - Contract

Arrival Manager

Air Navigation Services

Air Navigation Service Provider

Approach

Airborne Separation Assistance System

Air Traffic Control

Air Traffic Controller

Air Traffic Flow Management

Air Traffic Management

Air Traffic Service Unit

Client Aviation System Enquiry

CTA/ATC System Integration Studies

Continuous Descent Approach

Communication Navigation Surveillance

Central Office for Delay Analysis

Controller Pilot Datalink Communication

Controlled Time of Arrival

Degree of Change

Direct Operating Cost

European Civil Aviation Conference

xiv

EPP

ETA

EU

FM1

FM2

FM3

FMS

I4D or i4D

IFR

KPA

LCC

LR

MUAC

NAS

NCOIC

NIMS

OFA

OSED

Extended Projected Profile

Estimated Time of Arrival

European Union

Flights Model 1

Flights Model 2

Flights Model 3

Flight Management System

Initial Four Dimensions

Instrument Flight Rules

Key Performance Area

Low Cost Carrier

Long Range

Maastricht Upper Area Control Centre

National Airspace System

Network Centric Operations Industry Consortium

Network Information Management Systems

Operational Focus Area

Operational Service and Environment Description

xv

PAX

PBN

R&D

R/T

RTA

RWY

SA

SES

SESAR

SJU

SWIM

TMA

Passenger(s)

Performance Based Navigation

Research and Development

Receiver/Transmitter

Required Time of Arrival

Runway

Single Aisle

Single European Sky

Single European Sky ATM Research

SESAR Joint Undertaking

System Wide Information Management

Terminal Manoeuvring Area

ToD

US

WP

Top of Descent

United States

Work Package

xvi


1

1 INTRODUCTION

1.1 Setting the Scene

1.1.1 A Brief Introduction to the European ATM

In the Air Transport value chain, the Air Traffic Management (ATM) framework

gathers the essential infrastructures of systems, people, and procedures, which

together with airports enable Air Transport and other aerial movements to

operate in a safe and efficient manner. ATM covers three main missions (Refer

to Figure 1-1 below that illustrates the global structure of ATM in Europe).

Figure 1-1 European ATM Global Structure

Source: Compiled by the author based on EUROCONTROL web pages (2013c)

2

The first mission of ATM is to control air traffic by managing the synchronisation

and the separation of aircraft, both on the ground and in the air.

The second mission of ATM is to manage and organise the airspace by

establishing permanent or dynamic airspace structures, in order to

accommodate the different types of air activities, the volume of traffic, and the

corresponding resources.

Finally, the third mission of ATM is to manage the air traffic flow and capacity by

creating an orderly flow of air traffic through orientation, ground departure

sequences, and balanced capacity management.

The Air Traffic Control (ATC), airspace management and Air Traffic Flow

Management (ATFM) services, which make up ATM, are provided in Europe by

Air Navigation Service Providers (ANSPs) and EUROCONTROL. These

organisations are responsible for organising and managing the safe and

efficient flow of aircraft in the air and on the ground. ATC is the most visible part

of Air Navigation Services (ANS) (EUROCONTROL, 2013c and SJU, 2013a).

Today, European aviation represents 790 million passengers and 3.2 million

workers. ATM is an integral part of the European aviation with 56,000 workers

(Griffiths, 2013). While European ATM currently handles approximately 26,000

flights daily, it is forecasted that EU traffic will significantly increase by 2020

(EUROCONTROL, 2013c).

3

1.1.2 The Recent European ATM Reform

In 2004, the EU Commission launched the Single European Sky (SES) under a

first legislative package (SES I) with ambitious initiatives aimed at reforming the

architecture of European ATM. SES I involves the implementation of a package

of measures, in order to satisfy the needs expressed by several stakeholders.

Firstly, the ANSPs, who want to provide a better quality of service at a lower

unit cost for airspace users. Secondly, the airlines, who want to meet the

demand with a better quality of service, better flight profiles, and hence, lower

fuel consumption. Thirdly, the airports, that want to optimise operations. Then,

the passengers, who would like the provision of a better service at a lower cost,

with increased safety and fewer delays. Finally the general public would like a

more environmentally-friendly system with less noise. These measures apply to

both the civil and military sectors, and cover the regulatory, safety, airport

capacity and technological aspects of aviation (SJU, 2013a). Within the ATM

framework, an ATM Master Plan has been defined, in order to cover all the

measures and expectations (Refer to Figure 1-2 below that illustrates the 4

different pillars of the ATM Master Plan).

Figure 1-2 EU Performance Scheme - ATM Master Plan Goals

Source: Compiled by the author based on the Building a Single European Sky presentation by Peter Griffiths (2013)

4

Under the first pillar, which deals with the regulation of performance, the EU

Commission has three different measures namely, to drive the performance of

the ATC system, to facilitate the integration of service provision, and to

strengthen the network management function.

Under the second pillar that aims to ensure a single safety framework, the EU

Commission stresses that the growth in air traffic, the congestion of airspace

and aerodromes, as well as the use of new technologies justify a common

approach to the development and application of harmonised regulation to

improve safety levels in air transport.

Regarding the third pillar, whose objective is to open the door to new

technologies, the EU commission notes that the present ATC system is being

pushed to its limits, working with obsolescent technologies and suffering from

fragmentation. As a result, Europe must speed up the development of its control

system.

Finally, under the fourth pillar that aims to manage capacity on the ground, the

EU commission insists that investment is necessary, in order to ensure that

airport capacity remains aligned with the air transport management capacity,

and to preserve the overall efficiency of the network.

Following this SES initiative, the SESAR Programme was launched in order to

find operational and technological solutions to cope with the growing demand

for air travel, as traffic is expected to significantly increase in Europe by 2030

(SJU, 2013a). In addition the SESAR Programme is a key step to boost air

traffic management in Europe, as the ATM has not been sufficiently improved

yet and the technologies used are becoming old and saturated.

5

1.2 Research Context

Within this ATM reform context of improving ATM in Europe and as part of the

SESAR Programme, several innovations have been launched and are currently

being thoroughly studied by many European actors, in order to prepare their

near future deployment in Europe. One of these outstanding innovations is the

initial 4D (i4D) Trajectory Management function, which is a key research project

within SESAR, and is on track to be implemented and deployed in the short-

term.

Led by Airbus and in association with related SESAR work packages, the i4D

Trajectory Management function is already well defined and is now undergoing

analysis by the Airbus performance team, in order to precisely assess benefits

and costs related to i4D operations. Nevertheless, at the same time, some

challenges and question marks still need to be clarified regarding the

deployment of the i4D function. In particular, the assessment of i4D operations

in a mixed equipage environment (i.e. equipped and unequipped aircraft) has

not yet been achieved by the contributors to the i4D project. In light of this need,

the research aim of the thesis has been defined with the Airbus team in charge

of the business evaluation of the i4D project.

Therefore, the outcome of the herein thesis research is a concrete added value

to the assessment of i4D operations in its near deployment phase. In addition,

the results stemming from this research are expected to contribute to the

initiation of further strategic and business studies regarding the deployment of

i4D operations in mixed fleets.

6

1.3 Research Limitations and Hypothesis

The herein research work only focuses on the European airspace in the context

of the SES and the SESAR Programme. As a result, no reference to the United

States counterpart programme (namely NextGen) is made in this thesis.

In addition, the hereafter study is based on a major hypothesis, namely that

efficient Arrival Manager (AMAN1) capabilities will be available and in service on

time for the deployment of the i4D function. Indeed, the feasibility and reliable

performance of i4D operations are based not only on efficient airborne systems

but also even more importantly on effective ground infrastructures (such as the

AMAN tool). Without the implementation of efficient AMAN capabilities, i4D

operations could not provide most of their resulting benefits as the

synchronisation between air and ground would not be optimised.

1.4 Research Aim and Specific Objectives

The overall aim of this research is to qualitatively analyse if i4D operations in a

mixed equipage environment will provide benefits to i4D-equipped flights

without penalizing unequipped flights during the entire i4D deployment phase.

In order to achieve this overall aim, specific objectives have been defined and

are listed below:

1 The AMAN is a dedicated support tool for arrival management, which provides sequencing

and metering capability for an airport. Optimised sequences are provided based on demand for

the runway at any given time, and on locally-defined optimisation criteria and input, such as

required runway throughput. The AMAN automatically tracks arrival aircraft progress and within

set rules it adjusts an aircraft’s position/time in the sequence, as required (SJU, 2012a).

7

Assess the overall benefit of i4D operations in mixed equipage

operations

Define the status for equipped/unequipped flights within the entire i4D

deployment phase, analysing the degree of change (positive or negative)

compared to today’s operations

Conclude on operation in mixed equipage related to the i4D function, by

identifying opportunities and risks

Suggest strategic principles related to the deployment of i4D operations

in mixed fleet, given the assessed implications and impacts from an

airline’s perspective.

1.5 Structure of the Thesis

Having introduced the research context and framework in Chapter 1, Chapter 2

provides an overview of the corresponding environment in addition to all

background information related to the main concepts that are discussed within

the research work.

Subsequently, Chapter 3 presents the methodology put in place, in order to

effectively satisfy the respective objectives of the thesis. Both the entire

experiment design and case-study scenarios are defined within this section.

Following on from Chapter 3, Chapter 4 addresses the results of the previous

analysis and discusses them from different points of view. In addition, an in-

depth fleet analysis focusing on EU airlines is described and discussed in this

section.

Finally, Chapter 5 provides a conclusion of the overall thesis work by

summarising the achieved contributions of the research. In addition,

recommendations for future research work and further activities in the

continuation of the obtained results are addressed in this final section.

9

2 LITERATURE REVIEW

2.1 An Overview of SESAR within the SES Context

Before describing SESAR in more details, the following summary tables are

offered for readers, in order to understand how SESAR differs from NextGen.

These tables highlight the main differences (Refer to below Table 2-1) between

the SESAR and NextGen Concepts of Operations, and also the main similarities

(Refer to below Table 2-2).

Differences

SESAR NextGen

Overall Goal

Perspective of the Concept

To achieve a performance-based European ATM System, built in

partnership, to best support the ever increasing expectations for air

transport with respect to the growing global mobility, in a safe, secure, and environmentally sustainable & cost-

effective manner

Strict ATM focus

Gate-to-Gate view with a window on the turnaround process

To achieve a Next Generation Air Transport System that meets the nations’ future air transport safety, security, mobility, efficiency, and

environmental needs

In addition to ATM, it also deals with other elements that may impact

ATM (such as Homeland Security)

Curb-to-Curb view (i.e. all aspects of airport terminal and passenger

operations)

10

ATM Service

Culture and Politics

U.S. Government is the only ANSP

Several member states that must agree

Many ANSPs

One nation from the start

Very Different

Industry Structure

More collaborative approach including for instance ATM ground

activities

More governmental approach

NextGen is more government-owned and driven

FAA funding is not cost-based

FAA includes regulation and service provision

Industry participation is through the NGATS Institute to avoid

competitive issues

Single military presence

Operational Concept

Time horizon

2020+ 2025+

Weather-related Data Acquisition

Information derived from a variety of traditional sources

Assessed as outside its scope of work

Centralized government-run weather single service is anticipated

Information and Data

More decentralized model

Establishment of a ATM Information Reference Model (within the SWIM

concept)

More centralized government-run approach

Table 1-1 Main Differences between SESAR and NextGen

Source: Compiled by the author based on documents from Ward (2008) and NCOIC (2008)

11

Similarities

Driving Need

High Growth of Air Traffic Demand by 2025

Global Market Opportunities

Tourism and Travel Growth

Regional Environment

Pressures (Affordability, environment, growth-capacity conflict)

Obligations (ICAO oversight)

Opportunities (Procedure improvement, advances in technology)

Commercial customers

Basic Objectives

Ensure safety (with increasing capacity)

Expand capacity

Protect the environment

Improve service for aviation customers

Global aviation harmonization

Information and Data

Emphasis on the information enabling the processes, interaction, and automated support of the ATM industry

Content of the information and the purpose of the content are very similar

Table 2-3 Main Similarities between SESAR and NextGen

Source: Compiled by the author based on documents from Ward (2008) and NCOIC (2008)

12

2.1.1 SES Performance Context

Initially, in 2005, the EU Commission expressed its political vision and set high-

level goals for the SES to be met by 2020 and beyond, namely:

Improve safety by a factor of 10

Enable EU skies to handle 3 times more traffic, which will also reduce

delays both in the air and on the ground

Cut ATM costs per flight by at least 50%

Reduce the environmental impact per flight by 10%.

(World ATM Congress, 2013)

Therefore, each above-listed goal represents an opportunity but conveys at the

same time a certain risk. Indeed, regarding the first goal, which is to improve

safety by a factor of 10, the related risk is to reduce capacity. For the second

one, which is to enable EU skies to handle 3 times more traffic, the related risk

is to increase risk of collision, as the sky will be more congested. Then, for the

third high-level goal which is to cut ATM costs per flight by at least 50%, the

related risk is to provide insufficient funding for operations. Finally, for the fourth

goal which is to reduce the environmental impact per flight by 10%, the related

risk is to reduce fuel margins (i.e. imposed margins of minimum on-board fuel to

airlines) (Griffiths, 2013).

As a conclusion, the overall goal of the SES performance scheme is to “drive

change in performance of Air Traffic whilst managing the risks of change, and

unwanted events” (Griffiths, 2013).

13

2.1.2 SESAR Programme vs. SESAR Joint Undertaking

The Single European Sky ATM Research (SESAR) Programme, founded by

both the European commission and EUROCONTROL in 2004 as a complement

to the SES legislation, is the operational and technological answer to the major

challenges of European air traffic growth. SESAR is one of the most important

research and development programme ever launched by the European

community.

The aim of this programme is to ensure the modernisation of the European ATM

system, which is not fundamentally changed since the 1960s, by coordinating

and concentrating all relevant research and development efforts within the

European Union. Indeed, the recent state of the EU aviation does not fit well to

the current and future society needs. In addition to increasing traffic the basic

technologies are obsolete, the EU airspace is fragmented, and ATC techniques

and procedures need to evolve in order to meet aviation challenges. Facing this

situation, it made necessary to handle coordinated and integrated research and

development activities at the EU level throughout the SESAR Programme (SJU,

2013a).

The objectives of the SESAR Programme are respectively to eliminate the

fragmented approach of the ATM and transform the European ATM system by

synchronising action plan of the different partners and combining their

resources, in order to reach ambitious business goals (SJU, 2013a). The

business goals of SESAR correspond to the high-level goals expressed by the

EU Community for the SES.

14

Sustainability and user-drive are key concepts of the SESAR approach (Airbus,

2012a). In addition, SESAR is all about partnership between five main

categories of actors (SJU, 2013b), namely:

Governments

ANSPs

Airspace Users

Airports

The Military.

Therefore, the SESAR Programme, which is the focal point managing all EU

ATM research and development efforts, is developing the new generation of

ATM system for the next 30 years by evolving the key Air Transport players in

R&D efforts.

Subsequently, in order to manage the SESAR Development phase, the

European Community and EUROCONTROL created the SESAR Joint

Undertaking (SJU) in 2007.

In addition to the two founding members (namely the European community and

EUROCONTROL), 15 other companies coming from different sectors are

members of the SJU Programme (Airbus, 2012a), namely:

ANSPs: NORACON2 (Northern Europe and Austria), DSNA (France),

DFS (Germany), NATS Limited (United Kingdom), ENAV (Italy), and

AENA (Spain)

Ground and Aerospace Manufacturing Industry: Indra, Natmig,

SELEX Sistemi Integrati, and Frequentis

Airports: SEAC (a consortium comprising six large European airports)

Airborne Equipment Manufacturers: Honeywell, and Thales

Aircraft Manufacturers: Airbus, and Alenia Aeronautica.

2 NORACON is a consortium of eight ANSPs: Austro Control and the North European ANS

Providers (NEAP), Avinor (Norway), EANS (Estonia), Finavia (Finland), IAA (Ireland), ISAVIA

(Iceland), LFV (Sweden), and Naviair (Denmark).

15

Regarding the objectives of the SJU Programme, the below-listed missions

have been stated by the SJU (SJU, 2013a):

Organise and coordinate the activities of the Development phase of

SESAR

Ensure the necessary funding for the activities of the Development phase

of SESAR in accordance with the ATM Master Plan

Ensure the involvement of the stakeholders of the ATM sector in Europe

Organise the technical work of research and development, validation and

study

Ensure the management of all R&D activities with a result-driven

approach.

Therefore, finally, as declared by the former Air Transport Director of the

European Commission in 2009, namely Daniel Calleja, the SJU “constitutes a

powerful public-private partnership which brings together all the stakeholders

from the ATM community, including ANSPs, aircraft manufacturers, airlines, civil

and military representatives, as well as the European Commission and

Eurocontrol” (SJU, 2013b).

16

2.1.3 SESAR Work Structure and Relationship with the Thesis Work

2.1.3.1 The SESAR Programme Overall Work Structure

When defining now the SESAR Programme structure, the three following

reference aspects are taken into account:

Operational ATM needs

R&D activities management

Technical coherency (i.e. homogeneity of systems in Europe).

As a result, the SJU defined the SESAR Programme structure around three

different dimensions. Firstly, the ATM Operational Services dimension, which

covers operational ATM needs and ensure coherent design of the ATM

Operational Services by projects in accordance with the SESAR concept.

Secondly, the Clusters dimension, which ensures technical coherence between

projects by controlling the R&D deliverables. Finally, the Work Packages

dimension, which organises the R&D activities into systems, operational,

transversal groups or projects (SJU, 2009).

The structure which enables the R&D activities for the definition and validation

of the ATM Target concept has been built upon the Work Packages dimension.

Therefore, the structure of the SESAR Programme is the following one, namely,

four different threads (Operational, Systems, SWIM3, and Transversal) which

classify the R&D Activities into 16 different Work Packages (WP) (Refer to

Figure 2-1 below that illustrates the overall Work Breakdown structure of the

SESAR Programme).

3 System Wide Information Management (SWIM) is a new concept covering a complete change

in the way of how information is managed within its full lifecycle and throughout the entire

European ATM system (EUROCONTROL, 2013c).

17

Figure 2-2 SESAR Programme – Overall Work Breakdown Structure

Source: Compiled by the author based on the SJU Presentation The Structure of the Work Programme (2009)

2.1.3.2 Relationship with the Thesis Work

Within the above overall structure of the SESAR Programme, the thesis work

refers to the Systems Thread breakdown and more precisely to the WP 9 that

deals with Aircraft. As part of the Systems thread, whose the objective is to

define and validate the systems that support the ATM Target Concept, the WP

9 covers the required evolutions of the aircraft platform and is organised into 26

different projects (SJU, 2009). Regarding the ATM part of the WP 9, the

objective is to perform several definitions and validations, such as a functional

analysis dealing with aircraft evolution, as well as contribution to overall

operational validation (SESAR Consortium, 2008).

18

In addition to addressing the progressive development of Aircraft Separation

Assurance (i.e. ASAS functions), and the aircraft components required for the

improvement of surface movement’s operations, the WP 9 deals with the

progressive introduction of 4D Trajectory Management functions among

airspace users (i.e. mainline, regional, and business aircraft), in order to provide

very precise 4D trajectory management capabilities (i.e. three spatial

dimensions + time). The thesis work is therefore directly linked to this project as

it deals with the initial deployment step of 4D Trajectory Management functions.

2.1.4 SESAR Phases and Concept Steps

Regarding the timeline, on the one hand, the SESAR Programme is organised

in the three following phases (SJU, 2013a):

The Definition phase, which began in 2006 and lasted 2 years, resulted

in the EU ATM Master Plan

The Development phase, which began in 2008, and is planned to run

until 2016. This research and development phase will result in new

operational procedures, technologies and pre-industrial components,

under the responsibility of the SJU

The Deployment phase, which will implement the results of the

Development phase and deliver the performance targets foreseen in the

ATM Master Plan from 2014 until 2025.

On the other hand, within the deployment phase of the SESAR Programme,

three different concept steps have been defined to describe the completion of

the target operational concept (Refer to Figure 2-2 below).

19

Figure 2-3 SESAR Concept Steps and their Relationship to the Deployment Baseline

Source: Compiled by the author based on the European ATM Master Plan Edition 2 (SESAR, 2012)

The Deployment Baseline consists of a set of operational and technical

solutions that are already available and being deployed (SESAR, 2013a).

The Step 1, namely time-based operations, focuses on predictability, flight

efficiency and the environment. The goal of this first step is” a synchronised

European ATM system where partners are aware of the business and

operational situations and collaborate to optimise their operations” (SESAR,

2013a).

The Step 2, namely trajectory-based operations, focuses on a further-evolved

predictability, flight efficiency and environment, in addition to adding capacity.

The goal of this second step is “a trajectory-based ATM system where partners

optimise "business and mission trajectories" through common 4D trajectory

information and user defined priorities in the network” (SESAR, 2013a).

20

The Step 3, namely performance-based operations, completes full SES

performance requirements. The goal of this final step is “the implementation of a

European high-performance, integrated, network-centric, collaborative and

seamless air/ground ATM system” (SESAR, 2013a).

It should finally be noted that, in the framework of the thesis, only Step 1 and

Step 2 (i.e. both time-based and trajectory-based operations) are considered in

the research study, as the i4D function has been only defined in the scope of

time-based and trajectory-based operations.

2.1.5 Airbus within SESAR

As part of its willingness to take part in the EU and US ATM modernisation

programmes (SESAR and NextGen respectively), which will require more

interactions and cooperation between aircraft and the ground, Airbus has set

the following objectives:

Define a future operational concept in order to make the best use of

existing and future aircraft capabilities

Implement future aircraft capabilities according to the future operational

concept

Synchronise respectively the air and ground development and related

deployment.

Within the SESAR Programme and the SJU, Airbus had a leading role in the

SESAR Definition phase and is still now a key player among SJU members for

the Development phase as the leader of the Work Package 9 (WP 9) and key

contributor to all operational projects and activities.

21

Subsequently, from 2014, Airbus will remain a key player within the Deployment

phase, in order to ensure the industrial deployment of mature innovations and

the synchronisation of the air and ground development.

Furthermore, in addition to participating in NextGen which plans to modernise

the US National Airspace System (NAS) through 2025, Airbus has exchanges

with Boeing in ATM, in order to ensure a worldwide interoperability and an

optimisation of ATM operations between the air and the ground.

Finally, Airbus created in 2010 a subsidiary named Airbus ProSky, in order to

support the deployment of the SESAR Programme. The Airbus ProSky Group

develops and supports globally modern ATM systems worldwide. In addition,

working closely with ANSPs, aircraft operators and airport authorities, Airbus

ProSky provides intelligent, ground-breaking ATM solutions that maximise

efficiency, capacity, and environmental benefits (Airbus, 2013c).

22

2.2 A Complete Overview of the i4D Function

In the near future ATM environment defined by the SESAR Programme, aircraft

will need to behave with an increased predictability. This requires that in

addition to following the trajectory cleared by the ATC, aircraft will need to fly

over waypoints at accurate times. This evolution is referred to as the 4-

Dimensional Trajectory concept (4D concept), meaning a three-dimensional

trajectory plus a target time (SJU, 2012b). As part of the full implementation of

4D operations, the initial 4D (i4D) function is the first implementation step

planned in this SESAR target concept.

2.2.1 Primary Projects Achieved

Before describing more deeply the i4D function and its related concept of

operations, it is interesting to take a look at previous projects and related

studies that have been achieved in the scope of the i4D function.

CASSIS

On the one hand, The CASSIS (CTA4/ATC System Integration Studies) project,

which was a partnership project activity from 2007 to 2010 and was operated

under the name EUROCONTROL's TMA 2010+ activities. This project

investigated and provided as a result requirements for improvements that can

be provided to the CTA concept for Terminal Manoeuvring Area (TMA)

operations. CASSIS is a typical project example of the approach aimed at

finding solutions that can take full advantage of existing technologies

(EUROCONTROL, 2008).

4 Controlled Time of Arrival (CTA) is an ATM imposed time constraint on a defined merging

point associated to an arrival runway (SESAR Lexicon, 2013b).

23

In the scope of this large project many air transport actors were involved such

as ANSPs, airlines, equipment manufacturers, and research organizations.

The CASSIS project was comprised of the following activities:

A concept of operations which describes CTA-based applications

Flight trials

The report which describes the flight trials, and their results.

Regarding the CASSIS-related flight trials, the use of CTAs was tested as a tool

in today’s ATM system using current technologies, and aircraft systems.

Throughout a set of three phases, those flight trials highlighted a number of

potential CTA-based applications, such as en-route delay using time as a

spacing tool. At the same time, a number of issues arose during the flight trials.

For instance, the need to combine CTAs with speed and altitude restrictions

during high traffic situations and a tendency towards increased workload for Air

Traffic Controllers (ATCOs) due to increased monitoring (EUROCONTROL,

2008).

Finally, the CASSIS project recommended, in addition to performing additional

fast simulations and real-time flight trials, to consider the CTA as a contract, and

to involve ground-related manufacturers within future CTA activities

(EUROCONTROL, 2008).

Project 5.6.1

On the other hand, based on work achieved throughout the CASSIS project, a

new project named P5.6.1 (in the framework of the Work Package 5 of the

SESAR Programme) started to perform iterative validation of concept elements

and processes related to the use of CTA time constraints in medium and high

complexity environments. P5.6.1 is now continuing to investigate the CTA

concept in addition to the i4D concept for TMA operations. The main focus of

the project is regarding the issue and execution of CTA constraints through the

use of airborne FMS Required Time of Arrival (RTA) capability (including i4D

24

capabilities with enhanced RTA capability). The main objective of P5.6.1 is to

enable the more widespread use of on-board aircraft time and trajectory

management capabilities, supported by appropriate ground-based systems, in

order to improve arrival management and sequence building, especially for

medium and high density operations (SJU, 2012a).

P5.6.1 members include EUROCONTROL, four ANSPs (DFS, ENAV, NATS,

and NORACON), and two aircraft manufacturers (Airbus and Alenia). In

addition, P5.6.1 has close dependencies with many other SESAR-related

projects (SJU, 2012a).

2.2.2 I4D Trajectory Management Function Definition

As a first definition, the i4D trajectory management function is a shared

ground/aircraft function expected to improve ATM by using a time constraint, in

order to precisely predict aircraft trajectories and communicate accurate 4D

trajectory information to the ground. This function will therefore enable aircraft to

fly optimal flight profiles (Airbus, 2012a).

While the first i4D operation is planned to be deployed within Europe from 2018

onwards, the overall aim of the i4D function is to provide significant early

benefits to ground and airspace users while being capable of being retrofitted to

suitable aircraft (namely among mainline and regional fleet) with limited costs.

The operational partners of the i4D project are the following main actors: Airbus,

EUROCONTROL’s Maastricht Upper Area Control (MUAC) centre, Honeywell,

Thales, NORACON, and Indra.

25

2.2.3 I4D Operational Concept Description vs. Today Operations

Firstly, globally, i4D operations can be considered as operations having/using a

trajectory exchange capability and having/using a CTA5/RTA element (SJU,

2012a). The scope of the i4D operating environment covers both en-route and

arrival phases. It should be noted as well that i4D operations are not limited to a

particular class of airspace (A to G). Furthermore, it is anticipated that the

majority of aircraft engaged in i4D operations will be IFR commercial air

transport flights operating in managed airspace (SJU, 2012a).

The global objective of i4D operations is to establish far in advance a sequence

for all aircraft converging to a merging point in a congested area (Honzik and

Herodes, 2012).

Regarding the operational concept, from a global point of view, i4D operations

are based on the assignment of a time constraint at a merging point to each

i4D-equipped aircraft after the coordination and synchronisation between the

aircraft and ground systems. As a result of this new procedure, it is expected

that aircraft will be allowed to fly their optimum profile up to the considered

merging point without any vectoring instructions from ATCOs (Honzik and

Herodes, 2012).

Honzik and Herodes’ paper is more related to the operational and technical

concept of i4D operations, while the herein thesis research is more strategic-

related, in order to assess impacts and how beneficial could be to progressively

integrate such i4D operations into Today ATM operations.

5 As additional information, CTA is the use of airborne RTA technology through the aircraft’s

Flight Management System (FMS) in order to self-manage to time constraints on waypoints that

are set by the ground system.

26

The overall objective of the Honzik and Herodes’ paper was to provide an in-

depth knowledge in order to understand how the i4D operations work

technically, and to demonstrate that such operations are very complex but that

first steps have been successfully validated, even if further validation campaign

and flight trials remain to be performed before the full deployment of 4D

operations. In addition to deeply describe the related principle of operations and

the applicable technologies implied (FMS, data communication tools); Honzik

and Herodes presented the results from the first flight trial in order to validate

the described prototype.

As a result of the P5.6.1, the following text has been formulated and agreed, in

order to define a common understanding of what is the i4D concept:

“The i4D concept is a concept ensuring trajectory information exchanges,

coordination, and reliable time-constraint management, between the air and the

ground. The reliable time-constraint management element uses an enhanced

RTA airborne functionality and enhanced ground arrival management

functionality and techniques. It is expected to provide improved efficiency,

predictability, safety and sequence management. It enables and uses:

2D Route consistency and synchronisation

3D Plan/constraint agreement

CTA/RTA with a known reliable performance accuracy

Trajectory prediction enhancements in ground systems and tools

Extended AMAN functions and use.” (SJU, 2012a).

Therefore, the i4D concept can be defined to be comprised of two core

elements.

On the one hand, a trajectory downlink from air to ground, which may be

used for multiple purposes including synchronised trajectory data (air and

ground having a common view of the trajectory), and for the use in ground

based on tools such as the AMAN.

27

On the other hand, the use of CTA/RTA within the context of Queue

Management activities, which is expected to improve related processes, and

to sequence traffic in the TMA airspace (SJU, 2012a).

Regarding now the detailed characteristics of the i4D operational concept, the

concept can be broken down into different steps throughout the progress of a

flight.

First of all, as part of the initialisation step occurring during the final en-route

flight phase (typically 10 minutes prior to Top of Descent (ToD)), the i4D-

equipped aircraft logs-on and establish a contract with the ATC ground system

via datalink exchanges (such as CPDLC6 or ADS-C7 messages). Upon the

successful completion of this initial process, the aircraft will then automatically

downlink the preferred 4D trajectory held in the FMS to the relevant ATC ground

systems by means of the Extended Projected Profile (EPP8).

The EPP downlink is triggered by a contract which is established during the

aircraft’s log-on process. The downlinked 4D trajectory within the EPP includes

the performance and operational information related to the business priorities of

the corresponding flight, and therefore represents a more accurate picture of

6 The CPDLC interface enables exchanges of short messages between the flight crew and the

ATCO. The messages can be generated automatically on request of either the flight crew or the

ATCO through a dedicated human interface. In addition, thanks to additional avionics installed

on board, the flight crew can instruct the FMS directly from clearances or directions received

from the ground.

7 The ADS-C communication mean enables exchanges of data reports between ground

systems and the aircraft, on the basis of a contract established and activated. The messages

are directly and automatically sent from the on-board system to the ground on regular intervals

or specific events. It must be noted that the only intervention on ADS-C is setting it off or

passing it in emergency mode.

8 The EPP is the ADS-C report containing the sequence of 1 to 128 waypoints or pseudo

waypoints with associated constraints or estimates (altitude, speed, time, etc…), as well as

estimate at ToD and speed schedule.

28

trajectory intention than the original flight plan. Then, on receipt of the EPP, the

relevant ATC ground systems perform a cross-check of the received trajectory

in comparison with the existing 2D reference trajectory held by those ground

systems. In the scope of the primary drivers for the i4D concept, the aim of this

cross-check is to ensure consistency between airborne and ground held

trajectories, in addition to enhancing safety. As a result of this cross-check, the

related ground systems will alert the appropriate ATCOs if any discrepancy in

the 2D lateral path is detected (SJU, 2012a).

Subsequently, upon completion of the previous ground-air 2D route

synchronisation check, the controlling Air Traffic Service Unit (ATSU) will uplink

a 3D plan to the aircraft via a CPDLC route clearance. The objective of this

uplink is that the aircraft is aware of the vertical constraints that the ground is

planning for the flight. On receipt of the CPDLC route uplink, the flight crew will

assess the implications of the uplinked message on the flight and will either

accept or reject it (SJU, 2012a). In most cases, it is expected that this uplink of

the 3D plan will simply represent another confirmation of the trajectory within

the filed flight plan. Following the complete ground/air synchronisation of the 3D

plan, the flight crew will send back to the relevant ATSU the updated EPP report

with updated FMS winds and temperatures data.

Then, the relevant ATSU will be now able to determine the location of the

metering point at which the aircraft will have to fly over. This location will vary

depending on the specific requirements of the operating environment (SJU,

2012a). As a result, in order to assign a fixed time constraint (namely a CTA),

the destination ground system of the controlling ATSU will first request via ADS-

C to the aircraft an Estimated Time of Arrival (ETA9) minimum and an ETA

maximum. ETA min and ETA max therefore represent a time interval where the

aircraft is confident to overfly the determined location of the metering point (Di

Meo, 2012).

9 The Estimated Time of Arrival (ETA) is the time computed by the FMS for the flight arriving at

a point related to the destination airport (SESAR lexicon, 2013).

29

Upon reception of the ETA min/ETA max window calculated and sent back by

the aircraft FMS to the ground, the AMAN will consider this reliable RTA window

in order to produce an overall optimal arrival sequence by assigning a CTA. As

a result, the relevant ATCO will issue the defined and assessed CTA to the

aircraft via a CPDLC message uplink containing the position and the time

required for the aircraft at the metering point (SJU, 2012a). On receipt of the

CTA uplink the flight crew will assess the impact of the request on their flight by

comparing it to current predictions. If everything is correct the flight will accept

the time constraint by responding with a CPDLC message to the ground. The

flight crew will also activate at the same time the RTA function in the FMS, and

the flight will adjust its trajectory accordingly (mainly in relation to its speed)

(SJU, 2012a). It must be noted that the aircraft will switch in standard

operations if anything is wrong or not agreed.

Finally, the aircraft with its assigned CTA will be managed and monitored by

airborne and ground systems. Every time a discrepancy in the trajectory is

detected from the existing agreed trajectory, the aircraft will send to the ground

a new updated EPP report, and therefore a resynchronisation of trajectories

between the air and the ground will be required as outlined before (SJU,

2012a).

Figure 2-3 below summarises the entire i4D operational concept described

above, by illustrating the different steps of exchanges between the air and the

ground that are required for i4D operations throughout the progress of a flight.

31

Figure 2-4 Different Steps of Air/Ground Exchanges throughout the Entire i4D Operational Concept

Source: Compiled by the author based on both the OSED Document (SJU, 2012a) and the FAST 50 Magazine (Airbus, 2012a)

32

Finally, regarding the actual differences between the existing operating methods

and those related to the i4D concept, Table 2-1 below outlines the key

conceptual differences in operating methods between today’s operations and

i4D operations.

Today Operating Method i4D Operating Method

Near exclusive use of Receiver/Transmitter (R/T) (i.e. traditional vocal radio communications only)

Use of advanced datalink communications (ADS-C/CPDLC) for routine communications. R/T usage by exception or in time critical scenarios

Ad-hoc visibility of airborne Flight Plan to Air Traffic Control actors (i.e. available request only)

Consistent visibility of airborne Flight Plan to ground actors/systems. Data is made available automatically through datalink contracts (ADS-C) for i4D-equipped aircraft

2D trajectory exchange followed by clearances

4D trajectory exchange followed by clearances for i4D-equipped aircraft

Time constraints (CTA) calculated without regard to the airborne capabilities

Enhanced AMAN calculating and proposing CTAs for all RTA capable aircraft before expected ToD to allow aircraft to self-manage to a time/point.

Time constraints (CTA) based on accurate aircraft performance capability; airborne provision of ETA Min/Max for i4D-equipped aircraft

Aircraft trajectory constrained by ground ATC/ATM processes such as arrival metering through tactical intervention techniques such as vectors and/or speed control etc...

Aircraft trajectory optimised by on-board systems (FMS) to respect ground ATC/ATM processes such as arrival metering and sequencing through time based constraints; aircraft self-manage to respect negotiated constraint

Table 4-2 Key Conceptual Differences in Operating Methods between Today’s

Operations and i4D Operations

Source: Compiled by the author using the Step 1 OSED Second Iteration Document, Operational Service and Environment Definition, SJU (2012a)

33

2.2.4 I4D Validation Steps through Flight Trials and Simulations

As part of the initial validation step of the i4D project, a first flight trial under

operational conditions has been performed in February 2012, in order to

validate the capability of the airborne systems to comply with time constraints

defined and negotiated with related ATC ground systems via air-ground datalink

communication (SJU, 2012c). It was the first flight in the world using a four

dimensional upgraded and optimised ATM technology, and a world premiere

within the on-going transformation of today’s ATM. This flight test offered a

concrete solution towards improving the existing EU ATM system which is

reaching its capacity threshold (Airbus, 2012b).

The dedicated Airbus A320 test aircraft flew from Toulouse to Stockholm (Refer

to Figure 2-4 below that highlights the related route flown).

Figure 2-5 Route Flown during the First i4D Flight Trial

Source: Airbus (2012d)

34

Along its flight, the test aircraft flew through the EUROCONTROL MUAC

airspace where the airborne and ground systems agreed on a first time

constraint at a merging point close to the Copenhagen airport. The aircraft then

continued into the Danish airspace to demonstrate an optimised descent to

Copenhagen. After reaching the first merging point, the aircraft climbed to a

cruise level from which it negotiated a second time constraint at a merging point

close to the Stockholm Arlanda Airport. The aircraft then descended into the

Swedish airspace in a fully optimised way until the second and final merging

point, and landed safely at Arlanda (SJU, 2012c).

As a result, throughout a successful enhanced collaborative work, this first i4D

flight contributed to demonstrate the technical and operational feasibility of the

concept by maturing both the technical definition and the system design, as well

as providing a first exposure to the operational community (Airbus, 2012c).

Then, following on from the completion of the first validation step, further

exercises have been performed at the end of 2012 with particularly combined

simulations between the Airbus simulator in Toulouse and the platforms used by

MUAC. The objective of this second i4D validation step has been to stretch the

boundaries of the i4D concept throughout the introduction of vectoring and level

changes, in order to refine the parameters for controlling a mixed mode

environment (EUROCONTROL, 2012).

Finally, as part of the third step throughout the i4D validation campaign, further

simulations are planned near the end of 2013 followed by a second flight trial.

This second flight trial is expected to test some of the prototype controller tools

currently under development, and to highlight increased automation in the 4D

trajectory negotiations between the air and the ground. In addition, a particular

focus will be considered regarding the management of different levels of

equipage throughout the fleet and the challenges associated with mixed mode

operations (EUROCONTROL, 2012).

35

2.2.5 Overall Benefit obtained from i4D Operations

Firstly, i4D operations are expected to improve the overall performance and

reliability of the AMAN system. Indeed, it has been assessed that it will give

better performance in the sequencing and scheduling of the arrival stream as

well as higher potential for equipped aircraft to fly optimised trajectories at

speeds and descent rates that save fuel and reduce noise. At the same time,

i4D operations are expected to provide all stakeholders with higher predictability

(SESAR, 2012).

Then, regarding the Capacity Key Performance Area (KPA), it is expected that

i4D operations will increase ATM capacity and flexibility by bringing enhanced

runway throughput due to better sequencing of arriving flights, less lateral

deviation, reduced stock holding, as well as an overall reduction of the ATCOs

workload (SESAR, 2012).This mainly concerns major airports.

Regarding the Flight Efficiency KPA, it is expected that the allocation of a CTA

before the ToD will allow i4D-equipped aircraft to fly a near idle profile (i.e. the

optimum profile integrating the time constraint and reducing the use of stock

holding) (SESAR, 2012). As a result, i4D-equipped aircraft will save fuel, and at

the same time they will have a less detrimental impact on the environment

(recording less noise and less CO2 emissions).

In addition, thanks to a better management of the arrivals it is expected that

i4D-equipped aircraft will be far less affected by holdings (i.e. operational delay

defined in terms of performance as a step at the green dot speed), as well as by

patch stretching (i.e. operational delay defined in terms of performance as a

distance extension at the current speed). As a result, i4D-equipped aircraft are

expected to record less arrival delays.

36

Finally, two other key benefits have been assessed by the SESAR Programme

in relation to i4D operations. On the one hand, regarding the cost effectiveness

KPA, it is expected that airlines operating the i4D function will benefit from a

reduction of their operating costs linked to ATM delays (i.e. ATM cost per flight).

On the other hand, i4D operations are expected to also provide a better

predictability which will balance more effectively the workload between ATCOs

according to the expected traffic.

37

2.3 Mixed Equipage

2.3.1 Overall Principle and i4D-Related Aircraft Equipage

Mixed equipage is unavoidable as new technologies and capabilities of

advanced systems are provided step by step into the air transport industry. The

principle of mixed equipage is hence defined globally as the mix of equipped

aircraft and unequipped aircraft which have to be managed, controlled and

integrated in the same airspace without penalizing each other.

As a more technical definition, the principle of mixed equipage can be seen as

the use of avionics which have different performance levels, namely aircraft

types of different ATM capabilities levels (i.e. different service levels). These

differences allow the overall ATM system to increase either airline efficiency or

airspace efficiency, or both (Airbus, 2013a).

Regarding now the applicability of the mixed equipage principle to the i4D

function, as it was seen previously within the description of the i4D operational

concept, i4D operations are based on the exchange of information between air

and ground systems for the purposes of data synchronisation, and for

subsequent time constraint management when required.

38

Regarding the airborne capabilities required for i4D-equipped aircraft, the

related necessary equipment elements are listed below:

A datalink connection capability, which supports logon and information

exchanges on CPDLC, and ADS-C capability

An ADS-C capable to downlink both a complete list of planned waypoints

with associated speed, altitude and ETA as contained in the EPP, and a

reliable ETA window (ETA min and ETA max) for one waypoint that has

been identified as the metering point by the relevant ATC

Enhanced FMS functionality including: enhanced RTA functionality, ADS-

C capable, and improved granularity of meteorological data/weather

modelling (SJU, 2012a).

Regarding unequipped aircraft it is considered, in the mixed equipage

environment that will surround i4D operations, that unequipped aircraft will be

conventional aircraft with conventional FMS capabilities (or no FMS at all), in

addition to being CPDLC capable. Indeed, a mandate exists for both airborne

and ground systems to be equipped with CPDLC from 2013, and before the

beginning of the i4D deployment expected in 2018 (SJU, 2012a). However, it

must be noted that this first CPDLC mandate will not support the i4D function

for now.

39

2.3.2 Previous General Theoretical Studies

Regarding interesting theoretical studies achieved in the scope of mixed

equipage operations, a NASA study published by Sir Kopardekar with other

scientists can be mainly underlined. This US research study analysed the

feasibility of mixed equipage operations under higher density in an automated

separation environment, using a human-in-the-loop simulation. Throughout this

in-depth study, it was demonstrated that mixed equipage operations are

feasible to a limit within the same airspace. While controllers are inevitably

limited in the management of mixed-equipped fleet, the simulation illustrated

that mixed equipage operations are feasible in the same airspace even under

significant higher traffic density conditions. Finally, the corresponding article

also revealed the following logical statement, “the higher the traffic density of

equipped aircraft, the lower the number of unequipped aircraft that can be

managed within the same airspace” (Kopardekar et al., 2009).

As a result, the latter will be applicable to the model definition of the hereafter

study as naturally the number of i4D-equipped aircraft will increase within the

deployment of the i4D function, and on the contrary the number of unequipped

aircraft will proportionally decrease.

41

3 METHODOLOGY

3.1 Overall Thought Process

Figure 3-1 below summarises the overall thought process which has been

defined by the author, in order to complete successfully the entire study.

Figure 3-1 Overall Thought Process

Source: Compiled by the author

42

Firstly, as part of the STEP 1, the scope of the study will be defined by listing

the different assumptions and limitations that have been considered for the

study. In addition, the Deployment Phases, the Flights Models and the Today

Base Model considered for Comparison will be carefully defined, in order to set

up the experiment design in mixed fleet operations.

Then, as part of the STEP 2, in order to define relevant key enablers and

bottlenecks to consider in the hereafter study, the potential target benefits

related to the implementation of i4D operations will be identified. As a result, the

key enablers and bottlenecks will be defined, as well as the three different

scenarios.

Upon completion of the STEP 2, the STEP 3 will be dedicated to the

performance of the comparative impact analysis for each case scenario

between the Today Base Model, and the different Flights Models. In this

analysis a segmentation of equipped/unequipped flights will be achieved, and

subsequently the degree of change compared to today’s operations in terms of

time benefit throughout the i4D deployment will be highlighted in accordance

with each case scenario.

As a result of the outcome stemming from the STEP 3, the STEP 4 will

conclude on the status for each Flights category related to i4D operations in a

mixed equipage environment by identifying opportunities and risks. In addition,

an overall risk assessment will be outlined on a global operational point of view

and related trails of further research study will be raised.

Finally, as part of the STEP 5, an in-depth fleet analysis will be carried out from

an airline’s perspective, in order to evaluate the implications and degree of

impact on the i4D implementation for EU airlines according to their related fleet

age breakdown and their type of operations. In addition, as a result of the

previous study on airlines, strategic deployment principles will be suggested as

ways to foster the initial deployment of the i4D function.

43

3.2 Scope of the Study: Assumptions and Limitations

On the one hand, regarding the operating environment applicable to the entire

study, the following limitations have been considered:

First of all, the study applies to the European sky only, and more

precisely to the ECAC airspace region (Refer to Figure 3-2 below that

highlights in blue member countries of the ECAC)

Figure 3-2 44 Member Countries of the ECAC

Source: EUROCONTROL (2013d)

44

Then, the AMAN Horizon (i.e. final En-Route + TMA airspaces) has been

selected as the studied Operational Focus Area (OFA) (i.e. 200 Nm from

the destination airport). Figure 3-3 below illustrates the operational area

considered throughout the study. It must be noted that the metering fix

corresponds to the metering point as well (common denomination).

Figure 3-3 Considered Operational Area – AMAN Horizon


Finally, in addition to the previous consideration, Figure 3-4 below shows

the referential flow of arrival sequencing which has been defined for

illustrating today’s operations. This referential flow is a typical arrival

sequencing at major airports (such as Heathrow) when considering same

aircraft types.

Figure 3-4 Considered Referential Flow of Today’s Arrival Sequencing


45

On the other hand, regarding airspace users, the study focuses only on

scheduled airlines (i.e. mainline and regional aircraft only).

Finally, regarding ground users (i.e. Airports and ANSPs), the study is limited

to the 30 largest EU airports only in terms of aircraft movements per year (as

stated by EUROCONTROL each year into the yearly Performance Review

Report). In addition, it is assumed that efficient AMAN capabilities will be

available and in service at those airports for the deployment of the i4D function.

3.3 Experiment Design in Mixed Fleet Operations

Having rigorously stated the scope of the study, namely the considered

limitations and assumptions, the second part in the framework of STEP 1 has

been to set up the experiment design in mixed fleet operations.

Before describing the successive elements defining the overall experiment

design in mixed fleet operations, it is necessary to carefully explain the

approach that has been followed, in order to complete the analysis hereafter.

First of all, the approach works on the basis that, flights are currently affected by

the ATC due to different reasons. An affected flight refers in the hereafter study

to a flight whose performances are degraded in terms of time, fuel consumption

and/or operational efficiency, i.e. a flight whose the entire continuity is not in

accordance with the initial flight plan.

In addition, the approach works on the basis that, if trajectories are known with

higher accuracy, it would be possible to build the ATM system around

aircraft/flights whose trajectory information are precisely known.

46

Therefore, the idea in the hereafter research is to reflect the typical breakdown

of affected flights in Europe nowadays, in order to analyse then how this

breakdown would be impacted by the implementation of i4D operations.

As a result, in the section 3.3.2 that deals with the design of the considered

Today Base Model (term defined by the author) reflecting the typical breakdown

of affected flights in Europe today, the recent figures of arrival punctuality and

the different delay causes at the arrival have been analysed respectively.

On the other hand, in order to design a relevant model in mixed equipage, it has

been necessary to take a look at the current breakdown of the aircraft/flights in

Europe, and to assess then what proportion of the considered fleet would be

possibly equipped with the i4D function. When looking at the current status of

the total fleet in Europe it is visible that, even if it only represents around 30% of

the total fleet (which comprises scheduled airlines (i.e. Single Aisle (SA), Long

Range (LR), and regional aircraft), business aviation, and general aviation), the

SA fleet covers the major proportion of flights in Europe. Indeed, the latter is

explained by the fact that, in addition to recording the higher number of aircraft

in operation throughout the EU sky, one SA aircraft typically completes on

average 8 flights per day while one LR aircraft achieves a maximum of 2 flights

per day only, and one regional aircraft on average 4 flights per day. Therefore,

throughout the hereafter analysis, it has been decided to focus on flights rather

than aircraft for the purpose of the study.

In addition, as part of the section 3.3.1 that deals with the definition of flights

models, it has been needed to segment aircraft according to how they will be

fitted to be equipped with the i4D function, namely to be either forward-fitted or

retrofitted. The purpose is to forecast the actual proportion of aircraft/flights that

would be equipped throughout the deployment of the i4D function. It must be

noted that a forward fit refers to a new aircraft which is already fully equipped

with the respective function or system when it emerges from the final assembly

line to be delivered, while a retrofit refers to an aircraft which has incurred

afterwards modifications to its initial on-board systems in order to be equipped

with the respective function or system.

47

0%

20%

40%

60%

80%

2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030

% of equipped flights - Total Fleet

% of equipped flights - Mainline & Regional Fleet (Scheduled Airlines)

3.3.1 Deployment Phases/Flights Models Definition

On the one hand, flights models combined with a segmentation of deployment

phases have been defined according to the fleet evolution forecasted by Airbus

related to the i4D implementation (Figure 3-5 below). Figure 3-5 illustrates a

comparative evolution between the total fleet and the mainline & regional fleet

only (i.e. scheduled airlines). While around 30% of total fleet is expected to be

i4D-equipped by 2030, almost 70% of total scheduled airlines in Europe are

expected to be equipped with the i4D function by 2030. Those forecasts are

based respectively on the expected number of forward-fitted aircraft and

retrofitted ones for each year in Europe among the SA fleet, the LR fleet, and

the regional fleet. In addition, the number of annual aircraft deliveries and the

number of expected annual retirements have been taken into account in the

forecast.

Figure 3-5 Fleet Evolution Forecast from 2018 to 2030 related to the i4D Deployment

Source: Airbus Internal Data - Airbus (2013b)

48

As a result of this forecasted evolution, it has been possible to sample the

expected progress of the i4D deployment with the following three different

samples:

Sample 1: 20% of total scheduled airlines-related flights will be i4D-

equipped in 2021


equipped between 2024 and 2025


equipped in 2030.

Therefore, based on these three extracted samples it has been possible to

segregate three different deployment phases, and to define three different

flights models as well. Tables 3-1 & 3-2 below summarise the defined

deployment phases and flights models respectively.

49

Deployment Phase 1 2018 - 2021



Table 3-1 Defined i4D Deployment Phases


Flights Model 1 (FM1)



Table 3-2 Defined Flights Models


50

On the other hand, for comparison purposes in the study hereafter, a base

model representing the situation of today’s operations has been built in terms of

on time performance at the arrival, and en-route flight efficiency.

Regarding the first criteria related to time performance at the arrival, the actual

all-causes arrival punctuality has been selected to be taken into account in the

base model definition. Table 3-3 below outlines the breakdown of actual all-

causes arrival punctuality in 2012 compiled by the Central Office for Delay

Analysis (CODA) on behalf of EUROCONTROL. This breakdown (not airport

specific) is based on a sample of commercial flights in the ECAC region whose

data was provided by airlines.

Proportion of flights ADVANCED (> 5min advanced) 39.7%

Proportion of flights ON TIME (within +/- 5min) 26%

Proportion of flights 5-15min DELAYED 17.7%

Proportion of flights 16-30min DELAYED 8.6%

Proportion of flights 31-60min DELAYED 5%

Proportion of flights >60min DELAYED 3%

Table 3-3 Breakdown of Actual All-Causes Arrival Punctuality in 2012

Source: Compiled by the author based on CODA Digest Annual Report 2012 – Delays to Air Transport in Europe – EUROCONTROL (2013a)

It must be noted that an arrival delay refers to a time difference between the

scheduled arrival time published by airlines and the actual on-blocks time at the

arrival.

Regarding the second criteria related to en-route flight efficiency, inefficiencies

of horizontal en-route flights has been selected to be taken into account in the

base model definition. It was assessed by EUROCONTROL that current flight

51

paths deviate from optimal paths by 3% to 5% on average (i.e. en-route

extension due to ATFM measures) (EUROCONTROL, 2013b).

In order to properly define afterwards the Today Base Model based on the two

previous criteria, it is relevant to assess before the proportion of delays related

to the area where the i4D function will have an impact, namely related to

ATC/ATM only. Figure 3-6 below illustrates the typical average breakdown of

arrival delay causes at the top 10 EU arrival airports with heaviest delays in

2012. The causes were reported by airlines to the CODA.

Figure 3-6 Average Breakdown of Arrival Delay Causes at the Top 10 EU Arrival Airports with Heaviest Delays in 2012

Source: Compiled by the author based on CODA Digest Annual Report 2012 – Delays to Air Transport in Europe – EUROCONTROL (2013a)

As a result, it is observable that only 15% are directly ATC related and

consequently i4D related. Nevertheless, due to potential time benefits provided

by i4D operations (less late arrivals of A/C), it can be also expected that a slight

proportion of reactionary-related delays (namely late arrival of aircraft, crew,

PAX or load) will be improved by i4D operations.

52

Therefore, taking into account all previous comments and data, a base model

for comparison representing the situation of today’s operations has been

defined as the breakdown of affected10 flights related to schedules airlines

within the ECAC airspace region in terms of on-time performance at the arrival

and en-route flight efficiency. It has been considered that strongly affected

flights include flights delayed by more than 30 minutes, and that slightly affected

flights include flights delayed by 5 to 30 minutes. Figure 3-7 below reveals the

Today Base Model considered for comparison.

Figure 3-7 Today’s Base Model Considered for Comparison


In the following analysis it has been assumed that the above breakdown is not

influenced by traffic growth due to continuous improvement in the air transport

industry.

10

Affected refers to a flight whose the entire continuity is not in accordance with the initial

planned behaviour (occurrence of ATC constraints, and different unexpected delays).

53

In addition, regarding i4D-equipped flights, it is expected that these flights will

not be affected as other flights. Indeed, as the aircraft trajectories of equipped

aircraft will be continuously synchronized and exchanged with the ground

throughout the entire flight (by means of the EPP), the ATC will initially build its

ATM system based on the trajectories of i4D-equipped aircraft. Therefore, it is

assumed that all i4D-equipped flights will be manageable without any troubles

at the beginning of the deployment until the percentage of i4D-equipped flights

reaches 20% of the total scheduled airlines-related flights. Then, as the number

of i4D-equipped flights will start to be quite significant, it cannot be assumed

that equipped flights will continue to not be affected at all. As a result, it is

assumed that, as soon as the percentage of equipped flights is above 20% of

the total scheduled airlines-related flights, 20% of the i4D-equipped flights will

be at least slightly affected. It must be noted that those assumptions and

considerations have been stated as basic.

As a recap, the following base statements have been assumed regarding the

affect breakdown of i4D-equipped flights:

When percentage of equipped flights is below 20% of the total scheduled

airlines-related flights: 100% of equipped flights are considered as “not

affected”

When percentage of equipped flights is above 20% of the total scheduled

airlines-related flights: 80% of equipped flights are considered as “not

affected” and 20% as “slightly affected”.

54

3.4 Identification of Key Enablers/Bottlenecks

As part of the STEP 2, it has been necessary to firstly identify the potential

target benefits related to the implementation of i4D operations, in order to

address the key enablers and bottlenecks that will be taken into account in the

analysis hereafter. Therefore, based on the SESAR overall validation targets

stated by the SJU (Refer to Appendix A), a theoretical analysis performed by

Airbus reported the different validation targets allocated only to the

implementation of i4D operations. Figure 3-8 below outlines these calculated

allocations to each SESAR KPA.

Figure 3-8 Validation Targets Allocated to i4D

Source: Compiled by the author based on Airbus Internal Data from Workbook B4.1 – Airbus (2013b)

Given the distribution of validation targets among the different KPAs (Figure 3-8

above), it has been decided to only focus on the major impacted areas

throughout the present study, namely on predictability, airspace capacity and

airport capacity. Subsequently, in the framework of future activities, further

studies focusing on cost effectiveness and fuel efficiency could be done.

55

Therefore, based on these identified target benefits from i4D operations, key

enablers and bottlenecks have been defined in relation to the implementation of

i4D operations.

On the one hand, regarding airspace/airport capacity, the following key drivers

have been considered:

The runway throughput as a bottleneck. Indeed, there is the presence

of physical constraints on the runway (minimum average spacing of

1min30sec between aircraft) due to waiting time between aircraft leaving

runway, and aircraft entering. The reason is to avoid strong wake

turbulence effects created by the aircraft taking off.

The en-route traffic synchronisation as an enabler. Indeed, significant

improvements are expected thanks to exchange of precise trajectory

information using the EPP.

On the other hand, regarding predictability, the following drivers have been

considered:

The flight duration as an enabler. Reduction of the flight duration is

expected thanks to reduction in variability of actual flight duration vs.

planned flight duration. Indeed, today, in order to secure a good

predictability, flight duration is constrained by buffers which are applied in

order to cope with any time fluctuation throughout the flight. As a result,

such buffers will be able to be reduced or even deleted in i4D operations.

Delays as an enabler. Indeed, reduction of operational delays (e.g.

holdings and path stretching) is expected with the implementation of i4D

operations.

56

3.5 Case-Study Scenario Definition

As a result of the previous identification of key enablers and bottlenecks which

need to be considered in the comparative analysis hereafter, three different

case-study scenarios have been defined, in order to consider additional variable

inputs on top of main i4D-related performance targeted benefits highlighted on

previous Figure 3-8.

Firstly the Scenario 1, as the downside case, whose the assumptions are the

following ones:

Hypothesis 1: No modification on the Arrival Sequencing (i.e. same

RWY throughput). This assumption considers that i4D operations will not

bring benefits at all on the Arrival Sequencing efficiency

Hypothesis 2: 30% of total equipped flights will be” slightly affected”

after Deployment Phase 1 is completed. This assumption is based on

what has been assumed and considered at the end of the section 3.3.2

in being a bit more pessimistic by increasing by 10% the percentage of

equipped flights that will be “slightly affected”.

Secondly the Scenario 2, as the baseline case, whose the assumptions are

the following ones:

Hypothesis 1: Arrival Sequencing efficiency will be improved by 1.5%

(i.e. 1.5% additional RWY throughput). This assumption has been stated

in assuming that realistically at least one or two slots will be added in the

current arrival sequencing as a result of the expected benefits provided

by i4D operations.

Hypothesis 2: 20% of total equipped flights will be “slightly affected”

after Deployment Phase 1 completed. This assumption is related to the

57

base statement that has been previously assumed and considered at the

end of the section 3.3.2.

Finally the Scenario 3, as the upside case, whose the assumptions are the

following ones:

Hypothesis 1: Arrival Sequencing efficiency will be improved by 3% (i.e.

3% additional RWY throughput). This assumption has been stated in

being a bit more optimistic than the related hypothesis in the scenario 2

Hypothesis 2: 15% of total equipped flights are “slightly affected” after

Deployment Phase 1 completed. This assumption is based on what has

been assumed and considered at the end of the section 3.3.2 in being a

bit more optimistic by decreasing by 5% the percentage of equipped

flights that will be “slightly affected”.

59

4 RESULTS OF THE ANALYSIS AND DISCUSSION

4.1 Impact Assessment

Based on the assumptions defined for each case scenario in addition to target

benefits figures allocated to the i4D implementation, an excel model has been

built for running each scenario (Refer to Appendix B that illustrates

corresponding data computation models).

It should be noted that the philosophy behind this model is a logical statistical

distribution between the three different categories of affected flights. In the excel

model the first distribution occurs at a global point of view depending on the

assumptions allocated to each case scenario. For instance in the first scenario,

as there is no increase in runway throughput, it is assumed that for the Flights

Model 1 (FM1) the breakdown of affected flight will not be changed compared to

today. As a result, assuming as well that equipped flight will not be affected at

all at the stage of FM1, the distribution within the breakdown of affected flights

for unequipped flights is calculated by spilling over one category to the other

according to what remaining proportion is allocated to unequipped flights. Then,

for the Flights Model 2 (FM2) and the Flights Model 3 (FM3), the starting point

of the distribution is also the breakdown from a global point of view. In those

cases, the target benefits figures allocated to the i4D implementation are taken

into account, as the proportion of equipped flights will be significant enough in

order to provide global benefits. As a result, the total of target benefits figures

allocated to the i4D implementation (namely 2% of predictability + 10% of

airspace capacity + 1.5% of airport capacity) is weighted according to the

respective proportion of equipped flights, and then added to the today total

proportion of the “not affected” category. Subsequently, the principle of spilling

over one category to the other is applied, in order to obtain a total of 100% for

each total breakdown. This overall statistical process has been then reiterated

for the scenario 2 and the scenario 3 respectively.

60

4.1.1 Scenario 1

Regarding the scenario 1, namely the downside case, Figure 4-1 below outlines

the resulting status for both equipped and unequipped flights through an

assessment matrix.

Figure 4-1 Scenario 1 Assessment Matrix - Equipped vs. Unequipped Flights


Therefore it is observable that, on the one hand, equipped flights will be “not

affected” at all for the FM1, as assumed previously in the methodology chapter.

Then, for both the FM2 and FM3, equipped flights will be mainly “not affected”

with only 1/3 that will be “slightly affected”, as assumed in the definition of the

scenario 1.

On the other hand, regarding unequipped flights, it is noticeable that at the

stage of the FM1 they will have more chances to be affected compared to today

(Refer to Figure 3-7 that represents the Today Base Model). Subsequently,

unequipped flights will have more chances to be “strongly affected” compared to

today for the FM2. In the case of the FM3, even if unequipped flights will have

61

slightly more chances to be “not affected”, the probability to be “strongly

affected” will be slightly higher in parallel compared to today.

Finally, regarding the results from a global point of view (i.e. grouping equipped

flights and unequipped flights together), Figure 4-2 below illustrates the related

results for each Flights Model.

Figure 4-2 Scenario 1 Assessment Matrix - Globally


Therefore it is observable that, even if at the stage of the FM1, the affected

flights breakdown will remain the same as today globally (due to no expected

improvement on the runway throughput), it will be slightly better for the FM2,

and even better for the FM3 with twice less flights “strongly affected”. This result

is explained by the fact that i4D-equipped flights will increasingly provide

benefits throughout the deployment of the i4D function, and at the same time

unequipped flights will be less and less numerous.

62

4.1.2 Scenario 2

Regarding now the scenario 2, namely the baseline case, Figure 4-3 below

outlines the resulting status for both equipped and unequipped flights through

an assessment matrix.



Therefore it is observable that, on the one hand, equipped flights will be “not

affected” at all for the FM1, as assumed previously in the methodology chapter.

Then, for both FM2 and FM3, equipped flights will be mainly “not affected” with

only 20% that will be “slightly affected”, as assumed in the definition of the

scenario 2.


stage of the FM1 they will have more chances to be affected compared to today

(Refer to Figure 3-7 that represents the Today Base Model). Subsequently,

unequipped flights will still have slightly more chances to be affected at the

63

stage of FM2. However, in the case of the FM3, unequipped flights will have

slightly more chances to be only “slightly affected” rather than “strongly

affected” compared to today.

Finally, regarding the results from a global point of view, Figure 4-4 below

illustrates the related results for each Flights Model.



Therefore it is observable that, at the stage of the FM1, the affected flights

breakdown will be already slightly better than today globally (due to an expected

slight increase of the runway throughput). Then, for the FM2, the respective

breakdown will be better globally as well, with 8% more flights “not affected”,

and almost twice fewer flights “strongly affected”. Finally, for the FM3, the

breakdown will be significantly better globally with 13% more flights “not

affected”, and only 2% of total flights “strongly affected” (compared to 10% in

today’s operations).

64

4.1.3 Scenario 3

Regarding finally the scenario 3, namely the upside case, Figure 4-5 below

outlines through an assessment matrix the resulting status for both equipped

and unequipped flights.



Therefore it is observable that, on the one hand, equipped flights will be again

“not affected” at all for the FM1, as assumed previously in the methodology

chapter. Then, for both FM2 and FM3, equipped flights will be mainly “not

affected” with only 15% that will be “slightly affected”, as assumed in the

definition of the scenario 3.


stage of the FM1 they will have slightly more chances to be affected compared

to today. Subsequently, at the stage of FM2, unequipped flights will have almost

exactly the same breakdown as today (Refer to Figure 3-7 that represents the

Today Base Model). In the case of the FM3, unequipped flights will then have a

65

slight better probability of being “not affected”, and the rest will be mainly

“slightly affected” only.

Finally, regarding the results from a global point of view, Figure 4-6 below

illustrates the related results for each Flights Model.



Therefore it is observable that, at the stage of the FM1, the affected flights

breakdown will be slightly better than today globally. Then, for the FM2, the

respective breakdown will be better globally as well, with significantly more

flights “not affected”, and 5% fewer flights “strongly affected”. Finally, for the

FM3, the breakdown will be significantly better than today globally with 17%

more flights “not affected”, and only 1% of total flights “strongly affected”

(compared to 10% in today’s operations).

66

4.1.4 Degree of Change during the i4D Deployment

Based on previous results obtained for each case scenario, another excel

model has been built, in order to illustrate the expected degree of change

(positive or negative) in the i4D deployment compared to today’s operations

(Refer to Appendix C that outlines the corresponding data computation model).

For instance, a Degree of Change (DoC) coefficient of 10 means 10 times

better than today’s operations. It should be noted as well that weight coefficients

have been added in the model, in order to accentuate more or less the

importance of each affect category. It was therefore decided to highly weight the

category “strongly affected” by a factor of 10, while weighting the two other

categories by a factor of 1 only. The reason for this allocation is to illustrate the

fact that a flight “strongly affected” will incur more significant operating costs,

and will therefore have a more detrimental impact on airline’s operations than

the two other categories.

67

0,0

5,0

10,0

15,0

20,0

Start FM1 FM2 FM3

DoC

i4D Deployment Timeline

Scenario 1 Scenario 2 Scenario 3

4.1.4.1 Equipped Flights vs. Unequipped Flights

Equipped Flights

Regarding equipped flights only, Figure 4-7 below illustrates the expected

Degree of Change during the i4D deployment compared to today.

Figure 4-7 Expected Degree of Change during the i4D Deployment – Equipped Flights


Therefore, it is observable that equipped flights will obtain significant time

benefits (highly positive) during the entire i4D implementation for every

scenario. However, it is noticeable that a slight decrease is expected within

Phase 2 (from FM2 to FM3), due to inherent traffic growth combined with a

homogeneous mix of equipped/unequipped aircraft within this period.

68

-10,0

-5,0

0,0

5,0

10,0

15,0

20,0

Start FM1 FM2 FM3

DoC



Unequipped Flights

Regarding unequipped flights only, Figure 4-8 below illustrates the expected

degree of change during the i4D deployment compared to today.

Figure 4-8 Expected Degree of Change during the i4D Deployment – Unequipped Flights


Therefore, apart from the downside scenario (namely Scenario 1) where

unequipped flights are expected to be negatively impacted enough, it is

observable that the i4D implementation would start to provide time benefits to

unequipped flights as well, as soon as i4D operations become largely deployed

(i.e. after FM2). This evolution is due to the fact that equipped flights will

increasingly improve ATM globally, and as a result unequipped aircraft, whose

their proportion will decrease within the i4D deployment timeline, will more and

more benefit from those improvements provided by i4D-equipped flights.

69

0,0

5,0

10,0

15,0

20,0

Start FM1 FM2 FM3

DoC



4.1.4.2 Globally

Finally, from a global point of view, it is noticeable (Figure 4-9 below) that, in all

case scenarios, the i4D implementation will increasingly improve positively

today’s operations by providing more and more significant benefits during the

i4D deployment.

Figure 4-9 Expected Degree of Change during the i4D Deployment – Globally


Therefore, Scenario 1 and Scenario 2, which are the most conceivable

scenarios, show that a significant improvement is expected globally regarding

i4D operations in a mixed equipage environment.

70

4.2 Opportunities and Risk Assessment

4.2.1 Status for Equipped Flights

On the one hand, according to the results provided by the previous study, Table

4-1 below summarises the respective assessed risks and opportunities for

equipped flights in relation to the i4D implementation.

Opportunities Risks

Not be any more affected along its

duration => smooth and optimized

flight

Be slightly affected along its duration in

Phase 2&3 due to possible inherent

conflicts difficult to manage by ATCs

Significant time/fuel savings

(better overall efficiency)

Better predictability ahead of time

Table 4-1 Opportunities and Risk Assessment – Equipped Flights


71

4.2.2 Status for Unequipped Flights

On the other hand, likewise according to the results provided by the previous

study, Table 4-2 below summarises the respective assessed risks and

opportunities for unequipped flights in relation to the i4D implementation.

Opportunities Risks

Obtain benefits in terms of flight

efficiency when the i4D function will be

largely deployed (after the completion

of Phase 2)

Have more chances to be affected than

today within the first part of the i4D

deployment

More direct routings and CDA possible

in low density airspace

Have lower priority than equipped flights

in high density airspace

Table 4-2 Opportunities and Risk Assessment – Unequipped Flights


72

4.2.3 Overall Risk Assessment and Trails of Further Study

Finally, as an overall risk assessment of the implementation of i4D operations

throughout a mixed equipage environment, the following points underline what

can constitute an obstacle or further required study, in order to fully assess the

future situation.

Firstly, it can be questioned whether or not ATC facilities will be able to cope

with both additional stimulated RWY throughput, and overall traffic growth.

Indeed, without suitable ATC facilities, it will not possible to effectively

implement and widespread the i4D function among airspace users.

Secondly, if prioritisation for i4D-equipped flights in the AMAN sequence is to be

agreed (i.e. give priority to the i4D-equipped flight over the unequipped flight at

the final sequencing), this would have a significant impact on AMAN

development and implementation (e.g. rules for i4D vs. non-i4D flights, and i4D

vs. i4D flights). As a result, it can be suggested, as further study, to find an

“appropriate” way of incorporating i4D-equipped flights in the AMAN sequence.

Finally, another risk associated to the implementation of i4D operations in a

mixed equipage environment, is the presence of “floated” flights and

perturbations in the AMAN sequence when increasingly introducing fixed-time

operations (i.e. more and more i4D-equipped flights). As a result, it can be

suggested, as further study, to assess the global impact of moving to a fixed-

time operation in terms of different equipage rates (i.e. benefits for a single flight

in a flow of traffic vs. impact on the entire flow).

73

4.3 Implications and Impact on the i4D Implementation from an

Airline’s Perspective

In order to assess the implications and impact from an airline’s perspective, an

in-depth fleet analysis of EU airlines has been achieved. As the implementation

of the i4D function in aircraft will depend on the age of each aircraft (retrofitting

more or less conceivable), the objective of the study was to mainly focus on the

expected fleet age breakdown when the i4D implementation will begin, namely

from 2018.

4.3.1 Scope of the in-depth Fleet Analysis of EU Airlines

In the framework of the fleet analysis, it was necessary to initially define the

scope of the study.

Firstly, as traditional scheduled carriers and LCCs account for 80.1% of total

flights in EU (Refer to Figure 4-10 below that outlines market share by aviation

segments in Europe in 2012), the study only focuses on traditional scheduled

airlines and low-cost airlines.

Figure 4-10 Market Share by Aviation Segments in Europe in 2012

Source: Compiled by the author based on Network Operations Annual Report 2012 – EUROCONTROL (2013e)

74

In addition, a criteria has been chosen for the selection of airlines, namely to

focus on the TOP 30 EU airlines in terms of weekly frequencies within Europe

(as June 2013, with more than 1000 flights per week intra EU). As this study is

only a first step for having a global perspective, the study is not airport specific.

The next step would be to focus only on specific major airports where i4D

operations are expected to be the most beneficial for airlines.

Then, a breakdown of fleet age has been defined, in order to categorise airlines

into the three following age-related groups:

Young Fleet: when more than 65% of the fleet is below 10 year-old

Old Fleet: when more than 65% of the fleet is above 10 year-old

Mixed Fleet: when the status is between the two previous definitions.

The 10-years threshold has been assumed as being a realistic limit, in order to

reflect the capacity to easily retrofit an aircraft.

Based on the previous definitions and selection, the fleet study has been

performed by analysing and extracting data from the Airbus Marketing tool

named Miki. This tool uses and combines databases from both internal

company data and external data services (such as OAG Aviation and CASE11).

Finally, additional considerations have been taken into account in the

framework of the analysis, namely the following ones:

Fleet in service as June 2013

Number of scheduled deliveries from 17 June 2013 to end 2018

Number of expected retirements from 17 June 2013 to 2018, assuming

retirement when:

A/C > 23 year-old for traditional scheduled airlines

A/C > 15 year-old for low cost airlines.

11

CASE = Client Aviation System Enquiry

75

4.3.2 Results for Traditional Scheduled Airlines

Regarding traditional scheduled airlines, Figure 4-11 below outlines the market

segmentation vs. fleet age of 21 airlines by presenting results in ascending

order of fleet average age.

Figure 4-11 Market Segmentation vs. Fleet Age for Traditional Scheduled Airlines – Expected to end 2018


Therefore, it is observable for instance that only three airlines out of 21

traditional scheduled airlines are expected to have more than 65% of their

respective fleet below 10 year-old. As a result, these 3 airlines would be the

ones who could get the most of benefits from i4D operations on their respective

operating costs, as they will be able to equip a large part of their fleet with the

i4D function.

76

Table 4-3 below summarises, as a result of the previous figure 4-11, the

outcome for the EU traditional scheduled segment expected in 2018 by

providing an assessment matrix of selected traditional scheduled airlines.

Young Fleet Old Fleet Mixed Fleet

Degree of Expected

Benefits on

Operating Costs

Moderate

Not Significant

Light

Number of Airlines

among the top 30

EU airlines

3 Airlines

8 Airlines

10 Airlines

Table 4-3 Assessment Matrix of Selected Traditional Scheduled Airlines – Results for Expected Status in 2018


Therefore, the positive impact of the i4D implementation over traditional

scheduled airlines is assessed as mitigated. Indeed, only 3 large traditional

scheduled carriers are expected to be able to obtain the majority of potential

benefits provided by i4D operations from 2018. Nevertheless, among the

current 21 largest EU traditional scheduled airlines in terms of weekly

frequencies, at least 10 are expected to obtain reasonable benefits from i4D

operations.

77

4.3.3 Results for Low Cost Airlines

Regarding low-cost airlines, Figure 4-12 below outlines the market

segmentation vs. fleet age of 9 airlines by presenting results in ascending order

of fleet average age.

Figure 4-12 Market Segmentation vs. Fleet Age for Low Cost Airlines – Expected to end 2018


Therefore, it is noticeable in the case of low-cost carriers that, 4 airlines out of 9

low cost airlines are expected to have significantly more than 65% of their

respective fleet below 10 year-old. As a result, these 4 airlines would be the

ones who could obtain the majority of potential benefits from i4D operations on

their respective operating costs, as they will be able to equip almost their entire

fleet with the i4D function. Furthermore, as Direct Operating Costs (DOCs) of

LCCs are more dependent on fuel costs than traditional scheduled airlines, the

degree of expected benefits on DOCs provided by i4D operations will be even

more significant for young low-cost airlines.

78

Table 4-4 below summarises, as a result of the previous figure 4-12, the

outcome for the EU low-cost segment expected in 2018 by providing an

assessment matrix of selected low cost airlines.

Young Fleet Old Fleet Mixed Fleet

Degree of Expected

Benefits on

Operating Costs

Significant

Not Significant

Moderate

Number of Airlines

among the top 30

EU airlines

4 Airlines

1 Airline

4 Airlines

Table 4-4 Assessment Matrix of Selected Low Cost Airlines – Results for Expected Status in 2018


Therefore, the positive impact of the i4D implementation over low-cost airlines is

assessed as strong. Indeed, among the current 9 largest EU LCCs in terms of

weekly frequencies, 4 are expected to obtain high benefits and 4 others to

obtain medium benefits.

Consequently, it is clearly observable that there are more low-cost airlines than

traditional scheduled airlines that would obtain significant benefits from i4D

operations from 2018. This result is pretty logical as low-cost airlines are

expected to be always much younger than traditional scheduled airlines in

2018.

79

4.3.4 Ways to Foster the Initial i4D Deployment – Strategic Principles

In this section, as a conclusion to the airline’s perspective, an extra thought was

carried out in order to state a couple of efficient ways that could be implemented

in order to foster the initial deployment of the i4D function among EU airlines.

The following is a set of non-exhaustive strategic principles that could foster the

deployment of i4D operations.

Firstly, in order to effectively launch the i4D deployment, it would be interesting

to offer incentives (during a limited time period) to airlines in order to balance

their return on investment & benefit to start operating i4D. Those incentives

could be from different nature, namely for example:

- Grants

- Use of charges reduction

- Participation to costs.

Regarding the sources of those types of incentives it could be provided either

by states (e.g. by the EU commission) or by banks (e.g. bank funding or private

funding).

Then, a strategic principle would be to generate interest for airlines because

first equipped airlines will benefit from incentives in addition to immediate

savings (as it was demonstrated previously within the report).

Finally, a warning can be addressed, namely to pay attention to the

synchronisation between ground and airborne systems (as a result of different

speeds of deployment between the two), in order to ensure an efficient

integration of i4D operations.

80

4.4 Further Discussion on Final Results – Sensitivity Analysis

4.4.1 Regarding Degree of Change throughout the i4D Deployment

As part of the first study, regarding the evaluation of the degree of change

throughout the i4D deployment compared to today’s operations, it can firstly be

noted that the weight coefficient has been a sensitive parameter. It has indeed

been observed that the modification of the respective assigned weight

coefficients has an impact on the graphs related to each flights segment mainly

(namely equipped flights or unequipped flights). While the tendency of the

graphs is all the same more or less stable when changing values of weight

coefficients, it can be pointed out in particular that the tendency of the graph

reflecting the degree of change globally remains closely the same whatever

assigned value of weight coefficient.

Then, the sensitivity of the input parameters (namely parameters defined within

the hypothesis of each case scenario) is reflected by the final results arising

from each case scenario. Indeed, it has been observed that, depending on the

assumed hypothesis, the tendency of each graph varies along the ordinate axis.

The purpose of defining three different scenarios from a pessimistic, neutral or

optimistic point of view has been therefore to take into account the sensitivity of

the input data. As a result, the graph obtained for the baseline scenario (namely

Scenario 2) has been considered as the most realistic case to efficiently

interpret the results, and conclude on the status for each flights segment as well

as globally.

It should finally be noted that the precise accuracy of each hypothesis

parameter or weight coefficient has not been considered as relevant throughout

this study because the core objective of the study has been to reflect

qualitatively (and not quantitatively) how the deployment of i4D operations will

impact mixed equipage operations.

81

4.4.2 Regarding the Fleet Analysis of EU Airlines

As part of the second study, related to the in-depth fleet analysis of EU airlines,

the first sensitive parameter has been the considered assumption regarding the

expected retirement threshold of aircraft. Indeed, depending on the age limits

considered for both traditional scheduled airlines and LCCs, the fleet age

breakdown will vary a little, and as a result the ranking of airlines will be maybe

different. Nevertheless, as the considered age limits are average common

values typically used in the air transport industry, the final results can be

considered as being well realistic, and the age limit assumption for retirement

can be considered as not being a significant sensitive parameter in the

achieved study.

Furthermore, the number of aircraft deliveries from June 2013 to end 2018 has

been another sensitive parameter. Indeed, depending on the number of

recorded deliveries for each airline, it more or less lowers the average age of

the respective total fleet, and therefore the final results of the analysis would be

different. Consequently, it should be noted that the deliveries taken into account

in this in-depth fleet analysis have been only those which have been recorded

into the Miki Airbus marketing tool as from 17 June 2013.

Finally, it can be pointed out that this fleet analysis has just been an initial

overall study, focusing on the age breakdown only. The study has not taken into

account the distinction between large airports and regional ones. As a result, a

further study could be to look at expected traffic of the different selected airlines

on major EU airports by 2018. Indeed, the objective would be to weight the

respective degree of benefits on operating costs, as the degree of benefits

provided by i4D operations will be much more significant for airlines that will

have a large market share on major EU airports.

83

5 CONCLUSION AND FUTURE WORK

5.1 Outcome of the Thesis and Conclusion on i4D Operations in

a Mixed Equipage Environment

In the context of the European ATM modernisation towards a Single European

Sky, and as part of the SESAR Programme, it was noticed during the literature

review related to the thesis work that the initial 4D Trajectory Management

function is one of the key pillars of the European ATM target concept for 2020

onwards. The primary projects related to this i4D Trajectory Management

function and the corresponding definition were then outlined before describing

in more detail the overall operational concept of i4D operations, which

essentially covers the en-route and TMA airspaces. The i4D operational

concept can therefore be described as being based on two major elements,

namely, a 3D flight plan synchronisation between the air and the ground

(consisting in exchanging datalink messages via advanced communication

technologies) combined with a controlling to time (using a CTA/RTA constraint

towards a metering point). Afterwards, global potential benefits obtained by i4D

operations were detailed in terms of overall performance, capacity, flight

efficiency, cost effectiveness, as well as predictability. In addition, still within the

scope of the literature review and for the purpose of the research work herein,

the principle of mixed equipage (i.e. equipped and unequipped aircraft) was

clarified.

After clearly explaining both the environment, the scope of the herein thesis and

the conducted approach, a first in-depth study was dedicated to the assessment

of the overall benefit of i4D operations in a mixed equipage environment. Within

this first study, the status for equipped/unequipped flights during the entire i4D

deployment phase was also defined, and the degree of change (positive or

negative) compared to today’s operations was analysed. As a result, the

analysis has proven, first that globally, the deployment of i4D operations would

84

positively improve the today’s situation by providing more and more significant

benefits throughout the entire deployment phase. Then, regarding the

distinction of equipage, it was evaluated that i4D-equipped flights would

naturally obtain significant time benefits (highly positive) during the entire i4D

deployment phase, given the assessed benefits provided by i4D operations and

listed in the literature review. At the same time, unequipped flights are expected

to be slightly more impacted by the implementation of i4D operations. However,

unequipped flights should also obtain benefits from the implementation of the

i4D function as soon as i4D operations become largely deployed (i.e. when the

percentage of i4D-equipped flights exceeds at least 50% of the total flights of

EU scheduled airlines). The reason for this expectation is a more predicted ATC

picture provided by i4D operations, that would allow ATCOs and relevant

ground systems to more easily incorporate unequipped aircraft traffic, and

would therefore decrease the impacts that those flights are facing on their

current trajectory. To conclude on this first study, and to entirely assess the

future situation, an overall risk assessment of the implementation of i4D

operations throughout a mixed equipage environment was performed, in order

to highlight possible obstacles as well as further required study.

Subsequently, a second study emphasised the fleet age breakdown of major

EU airlines, in order to assess the implications and the degree of impact of the

i4D implementation on the different selected airlines. As a result of this in-depth

fleet analysis focusing on the two major types of EU airlines, the i4D

implementation should have a stronger positive impact on the LCCs than the

traditional scheduled airlines. Indeed, among the top 30 EU airlines in terms of

weekly frequencies intra EU, only 3 out of 21 large traditional scheduled carriers

are expected to be able to obtain the majority of potential benefits from i4D

operations on their respective operating costs from 2018, in comparison with 4

out of 9 regarding low cost carriers. It was evaluated as well that the degree of

expected benefits on DOCs provided by i4D operations should be more

significant for the 4 youngest LCCs than the 3 youngest traditional scheduled

airlines, as those low-cost airlines will be able to equip almost their entire fleet

with the i4D function in 2018. Finally, as a conclusion to the airline’s

85

perspective, different strategic principles have been suggested, in order to

foster the initial deployment of the i4D function among the EU airlines, such as

offering different types of incentives to first-equipped airlines only, and

stimulating competition between suitable airlines which are expected to

immediately obtain most of the benefits from i4D operations within the first

phase of the deployment.

5.2 Recommendations and Next Steps

On the one hand, in the continuation of the in-depth fleet analysis achieved in

this thesis, further studies can be suggested. The first suggestion would be to

launch a marketing campaign on particular target airlines identified from the

completed study herein, in order to demonstrate that they could obtain

significant benefits by equipping their suitable fleet with the i4D function as early

as the deployment of the i4D function. Within the scope of this marketing

campaign, a second suggestion would be to develop in-depth business cases

related to selected airlines by underlining specific operational & cost benefits.

On the other hand, the assessment of benefits and improvement related to i4D

operations in a mixed equipage environment has been limited to a qualitative

approach only, due to limited time and resources. As a result, the next step

should be to perform further advanced studies and a quantitative assessment of

precise time and cost savings that i4D-equipped or unequipped aircraft could

obtain from i4D operations in mixed fleet. In the scope of these further

advanced studies, the applicable Airbus performance team is currently

continuing to precisely assess i4D-related benefits for different concrete

operational scenarios. In addition, the next step is to launch fast-time studies

within different actual airspaces using i4D models. For instance, Airbus,

EUROCONTROL and other partners are planning to launch shortly such an

advanced fast-time study within the Paris CDG airspace.

86

Finally, regarding future work planned in the scope of the 4D Trajectory

Management function, it can be underlined that further flight trials are expected

to occur within the coming months. In particular, real i4D integration is planned

to take place as part of a flight trial with ENAV (i.e. the Italian ANSP) in 2014. In

addition, the full 4D project is expected to be launched within Airbus from

October 2013, in order to begin to define the next requirements and

development phases before the implementation of the full 4D function in the

continuation of the i4D deployment.

87


89

REFERENCES

Airbus (2012a), “The 4D Trajectory Management”, FAST Airbus Technical

Magazine, Issue 50, pp. 10-14.

Airbus (2012b), Airbus takes Air Traffic Management to the fourth dimension

(Airbus Internal press release), Airbus, Toulouse, France.

Airbus (2012c), SESAR JU - Initial 4D (PowerPoint presentation presented by

an Airbus experimental test pilot), 6 March 2012, Amsterdam.

Airbus (2012d), SESAR 4D Trajectory – Airbus development and participation

to Scandinavia i4D trials (Airbus Internal PowerPoint presentation), Airbus,

Toulouse, France.

Airbus (2013a), Mixed Equipage Operation (internal working paper provided by

the ATM & MPP Department), Airbus, Toulouse, France.

Airbus (2013b), Workbook B4.1 & PCP Final Fleet Equipage (internal data

provided by the Airbus ATM Engineering Department), Airbus, Toulouse,

France.

Airbus (2013c), Airbus Environmental Innovations, January (Airbus internal

brochure), p. 4.

Di Meo, G-A. et al. (2012), Interoperability of military aircraft versus future air

navigation system (FANS), ICAS 2012, available at

http://www.icas.org/ICAS_ARCHIVE/ICAS2012/PAPERS/309.PDF (accessed

29th June 2013).

http://www.icas.org/ICAS_ARCHIVE/ICAS2012/PAPERS/309.PDF

90

EUROCONTROL (2008), CTA/ATC System Integration Studies (CASSIS) Flight

Trials Report, available at

http://www.eurocontrol.int/tma2010/gallery/content/public/image/Docs/Cassis%2

0Flight%20Trials%20Report%20v1.0.pdf (accessed 25th June 2013).

EUROCONTROL (2012), “Focus: I4D Test Flight Heralds New Era in Air Traffic

Management”, Skyway Magazine No. 58, Winter, available at

http://www.eurocontrol.int/documents/skyway-no-58-winter-2012 (accessed 27th

June 2013).

EUROCONTROL (2013a), Delays to Air Transport in Europe, CODA Digest

Annual Report 2012, available at http://www.eurocontrol.int/documents/coda-

digest-annual-2012 (accessed 4th June 2013).

EUROCONTROL (2013b), Performance Review Report 2012, available at

https://www.eurocontrol.int/documents/performance-review-report-prr-2012

(accessed 23rd May 2013).

EUROCONTROL (2013c), Single European Sky, available at

http://www.eurocontrol.int/dossiers/single-european-sky (accessed 1st July

2013).

EUROCONTROL (2013d), ECAC Member States, available at

http://www.eurocontrol.int/articles/member-states (accessed 9th July 2013).

EUROCONTROL (2013e), Network Operations Annual Report 2012, available

at http://www.eurocontrol.int/documents/network-operations-report-annual-2012

(accessed 6th June 2013).

http://www.eurocontrol.int/tma2010/gallery/content/public/image/Docs/Cassis%20Flight%20Trials%20Report%20v1.0.pdf

http://www.eurocontrol.int/tma2010/gallery/content/public/image/Docs/Cassis%20Flight%20Trials%20Report%20v1.0.pdf

http://www.eurocontrol.int/documents/skyway-no-58-winter-2012

http://www.eurocontrol.int/documents/coda-digest-annual-2012

http://www.eurocontrol.int/documents/coda-digest-annual-2012

https://www.eurocontrol.int/documents/performance-review-report-prr-2012

http://www.eurocontrol.int/dossiers/single-european-sky

http://www.eurocontrol.int/articles/member-states

http://www.eurocontrol.int/documents/network-operations-report-annual-2012

91

Griffiths, P. (2013), Building a Single European Sky (lecture attended at

Cranfield University in May 2013), Cranfield University.

Honzik, B. and Herodes, M. (2012), “Airborne 4-Dimensional Trajectory

Management”, 31st Digital Avionics Systems Conference, available at

http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6382317 (accessed

2nd July 2013).

Kopardekar, P., et al. (2009), “Feasibility of Mixed Equipage Operations in the

Same Airspace”, Eighth USA/Europe Air Traffic Management (ATM) Research

and Development Seminar, available at

http://www.atmseminar.org/seminarContent/seminar8/papers/p_089_DACM.pdf

(accessed 3rd July 2013).

NCOIC (2008), “Comparison of the SESAR and NextGen Concepts of

Operations”, available at http://www.skybrary.aero/bookshelf/books/2378.pdf

SESAR (2012), European ATM Master Plan Edition 2, available at

https://www.atmmasterplan.eu/ (accessed 10th July 2013).

SESAR (2013a), About the ATM Master Plan, available at

https://www.atmmasterplan.eu/about (accessed 10th July 2013).

SESAR (2013b), SESAR Lexicon, available at

http://www.eurocontrol.int/lexicon/lexicon/en/index.php/SESAR (accessed 11th

July 2013).

SESAR Consortium (2008), Work Programme for 2008-2013, available at

http://www.eurocontrol.int/sesar/gallery/content/public/docs/DLM-0710-002-02-

00-D6.pdf (accessed 10th July 2013).

http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6382317

http://www.atmseminar.org/seminarContent/seminar8/papers/p_089_DACM.pdf

http://www.skybrary.aero/bookshelf/books/2378.pdf

https://www.atmmasterplan.eu/

https://www.atmmasterplan.eu/about

http://www.eurocontrol.int/lexicon/lexicon/en/index.php/SESAR

http://www.eurocontrol.int/sesar/gallery/content/public/docs/DLM-0710-002-02-00-D6.pdf

http://www.eurocontrol.int/sesar/gallery/content/public/docs/DLM-0710-002-02-00-D6.pdf

92

SESAR Joint Undertaking (SJU) (2009), The Structure of the Work Programme

(PowerPoint presentation), available at http://www.powershow.com/view/89fb0-

YThlM/The_Structure_of_the_Work_Programme_powerpoint_ppt_presentation

(accessed 10th July 2013).

SJU (2012a), Operational Service and Environment Definition, Step 1 OSED

Second Iteration Document, Provided by the Airbus ATM Engineering

Department, Airbus, Toulouse, France.

SJU (2012b), I-4D – Flying a new dimension, SESAR Factsheet N°1/2012,

available at http://www.sesarju.eu/sites/default/files/documents/highlight/i4d-

factsheet.pdf (accessed on 2nd July 2013).

SJU (2012c), Take-off for the world’s first 4D flight, SJU Press Release,

Brussels, Belgium.

SJU (2013a), e-learning Module 1 about SESAR (Video), available at

http://www.sesarju.eu (accessed from May to July 2013).

SJU (2013b), Background on the Single European Sky & History about the SJU,

available at http://www.sesarju.eu (accessed 2nd July 2013).

Ward, D. (2008), “Comparison of NextGen and SESAR Modernisation

Initiatives”, FAA presentation available at

http://www.docstoc.com/docs/115008447/Comparison-of-NextGen-and-SESAR-

Modernisation-Initiatives

http://www.powershow.com/view/89fb0-YThlM/The_Structure_of_the_Work_Programme_powerpoint_ppt_presentation

http://www.powershow.com/view/89fb0-YThlM/The_Structure_of_the_Work_Programme_powerpoint_ppt_presentation

http://www.sesarju.eu/sites/default/files/documents/highlight/i4d-factsheet.pdf

http://www.sesarju.eu/sites/default/files/documents/highlight/i4d-factsheet.pdf

http://www.sesarju.eu/

http://www.sesarju.eu/

http://www.docstoc.com/docs/115008447/Comparison-of-NextGen-and-SESAR-Modernisation-Initiatives

http://www.docstoc.com/docs/115008447/Comparison-of-NextGen-and-SESAR-Modernisation-Initiatives

93

World ATM Congress (2013), SESAR Performance Framework, Workshop SES

(PowerPoint presentation), available at http://www.sesarju.eu/atc/sesar-

workshops (accessed 9th July 2013).

http://www.sesarju.eu/atc/sesar-workshops

http://www.sesarju.eu/atc/sesar-workshops

95

APPENDICES

Appendix A SESAR Overall Validation Targets

Source: Compiled by the author based on the World ATM Congress 2013 SESAR

Performance Framework document, SJU (2013)

96

Appendix B Data Computation Model for Impact

Assessment

B.1 Scenario 1

Scenario 1

FM1

20% i4D Equipped Flights Globally Status for Equipped Flights Status for Unequipped Flights

% Flights Not Affected

60% 100% 50%

% Flights Slightly Affected

30% 0% 37.5%

% Flights Strongly Affected

10% 0% 12.5%

FM2


% Flights Not Affected 64% 70% 57%

% Flights Slightly Affected 28% 30% 26%

% Flights Strongly Affected 8% 0% 17%

FM3





97

B.2 Scenario 2

Scenario 2

FM1





FM2





FM3





98

B.3 Scenario 3

Scenario 3

FM1





FM2





FM3





99

B.4 Additional Details of the Excel Model

100

101

Appendix C Data Computation Model for Degree of

Change Assessment

Degree of Change (DoC)

Today Base Model Weight Coefficient

% Flights Not Affected 60% 1

% Flights Slightly Affected 30% 1

% Flights Strongly Affected 10% 10

Globally Status for Equipped Flights Status for Unequipped Flights

Scenario 1

Start DoC 0.0 17.0 0.0

FM1 DoC 0.0 17.0 -4.3

FM2 DoC 2.3 11.0 -6.4

FM3 DoC 6.6 11.0 -1.8

Scenario 2

Start DoC 0.0 17.0 0.0

FM1 DoC 1.0 17.0 -3.0

FM2 DoC 5.2 13.0 -1.4

FM3 DoC 9.5 13.0 1.8

Scenario 3

Start DoC 0.0 17.0 0.0

FM1 DoC 1.3 17.0 -2.6

FM2 DoC 6.3 14.0 0.9

FM3 DoC 11.5 14.0 6.7

102

END OF REPORT

Date post:	25-Dec-2015
Category:	Documents
Upload:	cristian-arginteanu
View:	33 times
Download:	0 times

Durville _R_2013.pdf

Documents