Transcript USER FORUM 2014

NM USER FORUM 2014
Cooperative Traffic Management (CTM)
Introduction
Chris Bouman
NM Head of Network Development
30/01/2014
Cooperative Traffic Management
Interdependent!
NM implementation project to further reduce need for regulation and
achieve important step towards time based operations
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
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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
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NM USER FORUM 2014
Using occupancy counts for STAM & MCP
To further reduce the need for ATFCM measures
Marcel Richard
Senior ATC Expert
30/01/2014
Use of Occupancy Counts – STAM and MCP
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
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)
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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.
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NM USER FORUM 2014
STAM Phase 2
System Supported Coordination on ATFCM measures
Marcel Richard
Senior ATC Expert
30/01/2014
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
Querying
and filtering
area
Incoming
and outgoing
Coordination
request
Notifications
Detail of the
item to be
coordinated
Topic area
Hotspots
and STAM
measures
Conversation
history and
Chat 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 2
Validation Exercise from 12 until 23rd May 2014
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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
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NM USER FORUM 2014
Predictability
Reducing the gap between the planning and execution of flights
Christian Faber
ATFCM Expert
30/01/2014
What is the problem?
 Lack of pre-departure FPL
updates can make the
predicted flight trajectory invalid
 Pilots are sometimes not
informed about changes to the
FPL such as a new RFL and so
cannot implement these
changes
 The vertical profile or the route
is not flown according to the
FPL information held by the
NMOC and ATC
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Why does it make a difference?
Actual profile
FPL profile
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What is the effect?
 ATC sectors are entered that are not on the flight profile
described by FPL
 The demand ATC experiences can be significantly 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’
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Why does it matter?
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An independent study has estimated that improved predictability will
provide the capability to increase sector monitoring values delivering:
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an increase of 5-10% in
local sector capacities
a reduction in delays
of 20-30 %
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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
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NM USER FORUM 2014
Predictability issues, impact on ATC
How 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
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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Our Objective:
Safety, fluidity, efficiency, dynamicity, equity
 By
 Proposing evolution in Airspace Structure, associated with better
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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Our Objective:
Safety, fluidity, efficiency, dynamicity, equity
 By
 Proposing evolution in Airspace Structure, associated with better
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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Our Objective:
Safety, fluidity, efficiency, dynamicity, equity
 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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Our Objective:
Safety, fluidity, efficiency, dynamicity, equity
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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
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Intruders: A safety Issue
Over-delivery
Overload
Final action
= ATC
clearance
ANSPs
NMOC
Crew
AO Ops
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Our Objective:
Safety, fluidity, efficiency, dynamicity, equity
 ANSP reactions:
 Decrease capacity
Flight
Plan is
not just a flying ticket!
 Take capacity
buffer
 Over-Regulate on all layers sectors
ATC reluctance
to apply STAM
measures
It should
be mutual
commitment
and
 Misjudgement on CFPS system
responsibility
for
safety
and
more
 Loss of Cooperation between ATC and AO
efficiency.
 Is it a good solution ? NO
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NM USER FORUM 2014
Results of SESAR Target Time (TT) Trials
Validating an important step towards Time Based Operations
Leo van der Hoorn
Validation Manager, SESAR Network Operations
30/01/2014
From CTOT to TT – Concept in a nutshell
Now:
Use (only) CTOT for time-based ATFCM
Time-based ATFCM
measure
Entry
Time
CTOT
congestion
Issues:
New:
• 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
Use Target Time at congestion
Time-based ATFCM
measure
Target
Time
CTOT
congestion
For trials:
• Target Time +/- 3 minutes
• Flight Crew aim to meet Target Times
• Arrival Regulations => input to sequencing
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From CTOT to TT – Expected Benefits
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For ALL Network actors: increase predictability
 More effective regulations
 Potential for capacity increase  decrease of regulations
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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,…)
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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
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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
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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
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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
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