NM USER FORUM 2014

NM USER FORUM 2014

Cooperative Traffic Management (CTM)Introduction

Chris BoumanNM Head of Network Development

30/01/2014

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Cooperative Traffic Management

Improvements that directly interact and can not be addressed independently:

Use of Occupancy Counts by ANSP/FMPs to better assess demand and minimise need for regulation (e.g. Mandatory Cherry Picking, STAM Ph1, some ANSPs use since 2011)

System Supported ATFCM Coordination for all actors involved in establishing ATFCM measures

Predictability improvements by addressing tactical deviations from the filed Flight Plan (ongoing since 2009)

Target Time operations to enhance predictability and in support of arrival sequencing

Inte

rdep

end

ent!

NM implementation project to further reduce need for regulation and achieve important step towards time based operations

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Presentations:

Marcel Richard (NM):

Use of Occupancy Counts for Short Term ATFM Measures

Mandatory Cherry Picking operations trial

STAM Phase 2: ensuring coordinated STAM Measures

Christian Faber (NM):

Flight Plan predictability: need and actions

Corinne Papier (DSNA)

Flight Plan predictability: example unpredictability impact and way ahead

Leo van der Hoorn (DSR)

Target Time trials: set-up and current findings

NM USER FORUM 2014

Marcel RichardSenior ATC Expert

30/01/2014

Using occupancy counts for STAM & MCPTo further reduce the need for ATFCM measures

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Use of Occupancy Counts – STAM and MCP

Wider use envisaged for benefit of AOs and network performance (at least EUR core by 2015, potentially all FMPs after that)

=> Basis for STAM Phase 2 (see later item)

Demand-Capacity balancing to identify needed ATFCM regulation => NMOC and FMP coordinate with AOs and Airports to reduce need & impact.

Still used most: “hourly Entry Counts” => all flights that exceed declared capacity to be regulated.

Occupancy Counts – more accurate demand picture => more focused solutions: only address specific flights.

STAM Phase 1: local flow control measures (e.g. TONB, MIT, etc) based on Occupancy Counts to prevent /remove current regulations – in use by some FMPs with very good results

1 min

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Mandatory Cherry Picking (MCP)

Enables limiting an ATFCM measure, addressing short peaks in ATC en-route sectors or Aerodromes, to only a few “cherry picked” flights instead of all flights that would normally be subject that regulation

Only the flights subjects to that measure will receive a CTOT from NMOC.

all other flights that would normally be captured in the regulated period are excluded (i.e. no slot!).

Results 2013 MCP trial (MUAC & Reims and NMOC, referred to earlier today):

=> 130 flights regulated instead of 2126 flights, saving 4666 delay minutes

Towards permanent procedures for short term benefits.

NM USER FORUM 2014

Marcel RichardSenior ATC Expert

30/01/2014

STAM Phase 2System Supported Coordination on ATFCM measures

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STAM Phase 2

STAM Editor with creation of What-if flights Situation Awareness Collaboration Forum for Coordination of the STAM

Measures

Complete the implementation of the STAM process

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STAM Measure Editor

Cherry Picked flights Precise and focussed Wider variety of

measure type Coordinated workflow AU’s preferences

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STAM Collaboration Forum

Detail of the item to be

coordinated

Conversation history and Chat area

Incoming and outgoingCoordination

request

Notifications

Topic areaHotspots and

STAM measures

Querying and filtering

area

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STAM What Airspaces Users can see

Flights captures in a

Hotspot

Flight subject to a STAM Measure

Measure Kind

Coordination Status

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STAM Phase 2Validation Exercise from 12 until 23rd May 2014

Paris FMP

Aix en Provence FMP

Bordeaux FMP

Reims FMP

Brest FMP

Roissy FMP/TWR

Geneva FMP

Geneva TWR

Zurich FMP

Karlsruhe FMP

Roma/Padua FMP

UK FMP

Gatwick TWR

MUAC FMP

After Validation STAM ready for deployment in CTM context

NM USER FORUM 2014

Christian FaberATFCM Expert

30/01/2014

Predictability Reducing the gap between the planning and execution of flights

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What is the problem?

Lack ofLack of pre-departure FPL updatesupdates can make the predicted flight trajectory invalid

PilotsPilots are sometimes not not informedinformed about changes to the FPL such as a new RFL and so cannot implement these changes

The vertical profileprofile or the route is not flownis not flown according to the FPL information held by the NMOC and ATC

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Why does it make a difference?

Actual profileFPL profile

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What is the effect?

ATC sectors are entered that are not on the flight profile described by FPL

The demanddemand ATC experiences can be significantly differentsignificantly different from what was expected - including over deliveries!

Lack of certainty about the real level of demand can lead ATC to apply sector capacity ‘buffers’capacity ‘buffers’

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Why does it matter?

An independent study has estimated that improved predictability will provide the capability to increase sector monitoring values delivering:

an increase of 5-10%increase of 5-10% in local sector capacitiescapacities

a reductionreduction in delaysdelaysof 20-30 %20-30 %

Note that flexibility

flexibility

remainsremains to deviate

from the FPL when

tactically necessary

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How can aircraft operators and pilots help?

Update the FPL whenever “appropriate” Inform pilots about all changes to the FPL affecting

the conduct of the flight

File it – Fly it !!

!

File it – Fly it !!

!

NM USER FORUM 2014

Predictability issues, impact on ATCHow lack of predictability affects ANSP attempts to reduce need for regulation and may lead to safety issue.

Corinne Papier

DSNA - Head of ATFCM Division 30/01/2014

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Our Objective: Safety, fluidity, efficiency, dynamicity, equity

By Proposing evolution in Airspace Structure, associated with better

capacities Selecting optimum ATC sector configuration based on Traffic

Demand and ATC staffing

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capacities Building ATC sector configuration based on AO demand and ATC

staff From planning phase to real time phase, cooperating with military

partners

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capacities Building ATC sector configuration based on AO demand and ATC

staffing From planning phase to real time phase, cooperating with military

partners Identifying excessive workload Acting on few selected flights to smooth the traffic (amount of flights

and complexity)

DSNA is a path finder in Dynamic ATFCM process which allows a gain of capacity while maintaining high level of safety towards our customers.

BUT….

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Due to

Flight plan non adherence ETOT/CTOT non adherence AO reactivity when receiving a CTOT (even with 0’mn of

delay) Fancy routings

FMPs and ATC are daily facing unpredictable and dangerous situations.

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Daily case AND massive effect

Typical peak hour summer time : KR flight list , from 10h to 12h

60 flights/26 intruders

Typical peak hour summer time : KR flight list , from 10h to 12h

60 flights/26 intruders

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Intruders: A safety Issue

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Final action = ATC

clearance

Final action = ATC

clearance

NMOCNMOCCrewCrew

AO OpsAO Ops

ANSPsANSPs

Over-delivery

Overload

Over-delivery

Overload

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ANSP reactions: Decrease capacity Take capacity buffer Over-Regulate on all layers sectors ATC reluctance to apply STAM measures Misjudgement on CFPS system Loss of Cooperation between ATC and AO

Is it a good solution ? NO

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Flight Plan is not just a flying ticket!

It should be mutual commitment and responsibility for safety and more

efficiency.

NM USER FORUM 2014

Leo van der HoornValidation Manager, SESAR Network Operations

30/01/2014

Results of SESAR Target Time (TT) Trials Validating an important step towards Time Based Operations

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From CTOT to TT – Concept in a nutshell

Now: Use (only) CTOT for time-based ATFCM

Entry Time

congestioncongestion

CTOT

dep

Time-based ATFCM measure

• Assumed profile not always the actual profile• Objective of CTOT not managed after take-off• Actual trajectory and sector entry time can significantly

deviate from intended ATFCM measure

Issues:

New:

Target Time

congestioncongestion

CTOT

dep

Time-based ATFCM measure

Use Target Time at congestion

For trials:• Target Time +/- 3 minutes• Flight Crew aim to meet Target Times• Arrival Regulations => input to sequencing

Over-regulation or Over-delivery,

unpredictability

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From CTOT to TT – Expected Benefits

For ALL Network actors: increase predictability More effective regulations Potential for capacity increase decrease of regulations

For airspace users: flexibility & flight efficiency Operational flight plan adapted to airline needs, meeting TT Effective regulations Better use of capacity Less holding, less ATC actions

(e.g. vectoring, separation,…)

For ATC (en-route/airports): potential local TT preferences exchange with NM Optimising local operations, based on local business rules

(e.g. arrival sequence, link to AMAN, XMAN)

In collaboration with Airspace Users

Potential drawbacks to be considered Workload for AO dispatch & pilots Impact on flight efficiency

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From CTOT to TT – SESAR Validation Trials

Live trials using real airport regulations

TT Trial Palma June 2013 3 Airlines (Airberlin, EasyJet, Air Europa) 129 measured flights under TTA Validated also the integration of AOP and NOP:

TT optimised to respond to airport business needs

Fair Stream TT Trial May-October 2013 3 Airlines (Air France, Lufthansa, Swiss) CDG/DSNA - Munich/DFS - Zurich/Skyguide 800+ measured flights under TTA Validated preliminary AMAN integration at CDG

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Validation Trials – Main Conclusions and further research

Ops procedures for TT sharing between NM/APT/AOC/Flight Crew:

Acceptable and applicable in real operational conditions

Network provided TT for airport regulations:

Can be used for airport impact assessment

And adjusted to optimise airport operations

Some lessons learned – Objectives for future trials Adherence to TT reduced by: DEP time fluctuation, Delta Plan/Execution,

ATC involvement Clear Predictability increase has been measured, but…overall network

impact & benefits to individual airlines still to be addressed (mid-2014)

Predictability at TTA fix not propagated to landing time predictability, reducing benefits for AO – May be solved by integration with AMAN

NM USER FORUM 2014

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