part i: the challenge - aci europe...
TRANSCRIPT
Classification: Internal
Alison Bates - Head of ATM Strategy and Deployment
Date 18th June 2018
Airspace hotspot management, the future of efficient airport operations
ACI World/Europe WAGA - Safety and Operations Forum
PART I: THE CHALLENGE
Classification: Internal
Airport Operating Challenges
3
Community &
environmental Impacts
Weather resilience
▪ Fog and low visibility
▪ CB activity
▪ Storms and strong
winds
▪ Snow and Ice
Changing traffic
profiles
▪ Increase in personal
flying vehicles
▪ Drone integration
▪ Mixed navigational
equipage & performance
Increase in passengers and
movements
▪ Infrastructure limitations
▪ Airspace limitations
▪ Need to align ground-air
capacity
▪ Licence to grow
▪ Local regulations
▪ Noise
▪ Air quality
▪ Visual impact
▪ National parks; areas of protection
PART II: THE OPERATING
TERRAIN
Classification: Internal
5
The Ground
(G)
Pier served:133Remote: 66Cargo: 15
Classification: Internal
6
The Airspace
(A)
Classification: Internal
7
Dynamic Demand
(D)
Classification: Internal
The Equation
Demand
G + A (capacity)
= v Hotspot = ATFCM (Flow rate)
V = variable
Classification: Internal
Let’s look closer at the typical demand patterns (1st wave)
43mins early
17mins early
25minslate
2mins early
22mins late
36mins early
13mins early
1234
567
6 early arrivals triggered a regulation that knocked on to 108 flights
Current ETFMS / CASA process allocates delays to 1st planned ETO, best served
25mins early
8
Classification: Internal
10
Approximately 65% of inbound flights arrive from Europe, 16% from North
America and 6% from the Middle East
1%
49%16%
14%
6%3%
3%Latin America &
Caribbean
Asia Pacific
Africa
3%
South Asia
North America
Europe
Domestic
Middle
East
2%
China
2%
Former Soviet
Union
Inbound flights by region of last port of call (2014)
50%<p<55%
55%<p<60%
65%<p<70%
p>70%
On time arrival
performance
p<50%
Source: IDAHO-CDM 2014
Area of circle is proportional the number of inbound flights from each region
Colour of circle represents the proportion of flights arriving within ±15 minutes of the scheduled time
60%<p<65%
Skewed
towards
early.
PART III: THE APPROACH
(example case study)
Classification: Internal
12
Current world – NMOC tools (CHMI Data)
>45 aircraft expected into the
stacks between 05:40-06:40which would have led to
increased airborne holding
shortly after
Classification: Internal
13
Airports Introduce new prediction tools linked to Network via AOP/ACDM & DCB
This equates to peak airborne
delay anticipated at 07:00
with a reduction shortly after
Typically this would trigger a
hotspot (Flow rate)
Demand Capacity Balancing tool
Airport FMP/
ACC
NMOC
Classification: Internal
Demand Capacity Balancing - Flight prediction ListFlights identified that were
predicted to arrive when
airborne delay was greatest.
We Hypothetically delayed
these flights to ensure they
would enter the stacks
slightly later than planned
Algorithm issued Target
Times that were back
calculated into iCTOT as
today.
Intelligence applied to assign
TTA’s based on equitable
ops.
Classification: Internal
Impact of the changes analysed
As can be seen from
the image, the peak
has been reduced
from 19min to 16.4min
Classification: Internal
(1) Currently applying Mach speed reductions for AMAN tactical flow management
(2) Apply TTA for AMAN tactical flow management
(3) Apply TTA for AOP sequencing; Apply CTOT for AOP sequencing
(4) Refine sequence for ATC flow management; TTA revision
(5) Refine sequence for ATC flow management; TTA revision
(1) Currently applying Mach speed reductions for AMAN tactical flow management
(2) Apply TTA for AMAN tactical flow management
(3) Apply TTA for AOP sequencing; Apply CTOT for AOP sequencing
(4) Apply CTOT to European Deps when needed to allocate delay or smooth arrivals. Apply TTA to long hauls to improve
punctuality or allocate delay/smooth arrivals
Queue Management – Airport/Network
DMAN
XMAN
Boundary
AOP/Airport DCBCTOT
COP ToD
IAF
FAF
AMANACC
ACC
Network Manager
FOC
TTA
FIR
Bo
un
da
ry
Long
Haul
TTA
Live Trials planned in Sept 18
and March 19 via SESAR PJ24
Change of mindset: working as one team
Airport
Airline/GH
ANSP
NMOC