ENRI Int. Workshop on ATM/CNS (EIWAC2013) 19-21FEB2013

EN-024

A Simulation Study on a Method ofDeparture Taxi Scheduling atHaneda Airport
Izumi YAMADA,Hisae AOYAMA, Mark BROWN,
Midori SUMIYA and Ryota MORI
ATM Department,ENRI
i-yamada

enri.go.jp

ENRI Int. Workshop on ATM/CNS (EIWAC2013) 19-21FEB2013

Outlines
Background and objectives– Characteristics of Haneda airport

Traffic management algorithm
Results of fast-time simulation experiment– Reduction of taxiing and queuing time
– Guarantee of takeoff time

Discussion
Conclusion
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ENRI Int. Workshop on ATM/CNS (EIWAC2013) 19-21FEB2013

Backgrounds
Corresponding R&D vision– ICAO ASBU(Aviation Systems Block Upgrades)
Module 80: Airport CDM (Collaborative Decision Making)
Module 15: AMAN/DMAN (Arrival/Departure Manager)– Corresponding R&D reports in Europe and the UnitedStates says…
Airport CDM is effective for improving efficiency andpunctuality of airport operation– CARATS (JAPAN: Collaborative Actions for Renovation of Air TrafficSystems)

Bottlenecks at congested airports and airspaces in the
Greater Tokyo Metropolitan area, etc. must be eliminated3ENRI Int. Workshop on ATM/CNS (EIWAC2013) 19-21FEB2013

Aims of the study
To examine a traffic management method
suitable for Haneda airport– Departure taxi scheduling

Expected performance
1. Reduction of taxiing time
Especially for departure

2. Transparency in takeoff time planning andexecution (guarantee of takeoff time)4

ENRI Int. Workshop on ATM/CNS (EIWAC2013) 19-21FEB2013

About Haneda airport (1/2)
The most congested airport in Japan– Over 1,000 movements per day– Origin and destination of major air traffic flow inJapan
SapporoMainly used for domestic airways

OsakaTokyo(Haneda)

FukuokaNaha5ENRI Int. Workshop on ATM/CNS (EIWAC2013) 19-21FEB2013

About Haneda airport (2/2)
Int’lterminal

Cargo
Domesticterminal

A-RWY
3,000mHangarPhoto: MLITT

C-RWY
3,000mComplex layout and operation– 4 runways (2 pairs of parallel runways)

D-RWY
2,500m3 or 4 runways constantly active
Interference between runways occurs frequently– Gates: densely located around terminal buildings

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ENRI Int. Workshop on ATM/CNS (EIWAC2013) 19-21FEB2013

Interference between runways
Example of southerly wind configuration
C-RWYGatesDomesticterminal
H A N GA R

Crossing offlight paths

A-RWYInternationalterminal

N

Departure flight path
Arrival flight path(considering go-around) 7

Simulated surface traffic flow
(simulator developed by ENRI)

Departure
Queuing Departure
ArrivalRunway occupation

Time(JST)

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ENRI Int. Workshop on ATM/CNS (EIWAC2013) 19-21FEB2013

Location of congestion at Haneda
Almost limited in the area before departure
runway– Relevant to apply taxi scheduling (queuemanagement) Departures (504 flights)

Mapping of taxiing timewith speed less than
10 [km/h](excl. pushback)9

ENRI Int. Workshop on ATM/CNS (EIWAC2013) 19-21FEB2013

Simplified congestion model
Focusing on takeoff queues– Dynamics of congestion will be determined by…
Takeoff capacity of runway system
Number of departures reaching takeoff queue– Takeoff capacity drops temporarily
due to interference with arrival flow

Gates

Final
approach

Apron/Taxiway
Takeoff queues
FIXED taxi times
w.r.t gate-runway pair

Runway system

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ENRI Int. Workshop on ATM/CNS (EIWAC2013) 19-21FEB2013

Runway capacity constraint model
Based on Gilbo’s capacity model– Count (#dep., #arr.) observations in 5 minute time
window, rejecting (0,0) as exception– Evaluate the proportion of each (#dep., #arr.) in total
Arrivals
observations

on D-RWY

#dep.
#arr.

01234

0

21.0%

11.6%

5.7%

1.2%

118.3% 17.1% 13.0%

5.4%

02

3.9%

1.5%

1.0%

00

300000Departuresfrom A-RWY(Simulation example,dep.: A-RWY, arr.: D-RWY)

Capacity constraint assumption#/53#/511ENRI Int. Workshop on ATM/CNS (EIWAC2013) 19-21FEB2013

Departure scheduling algorithm 1/2
Taxi time
table

Predictedflow

Runway capacity
modelQueue
prediction

Takeoff time
window
assignment

Block-outtime assignment

Final
approach
Arrivals

Gates

Apron/Taxiway

Actualflow
Takeoff queues

Departures
Runway system

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ENRI Int. Workshop on ATM/CNS (EIWAC2013) 19-21FEB2013

Departure scheduling algorithm 2/2a) Predicted interfering landing number per 5 minutes
One arrival within
5-minute window… 18:45

Queue
prediction

32

54… 18:45

19:30… time

6987

19:00

One departure within
13
5-minute window1219
11 151822
10 14 16 17 202119:15
19:30 … timec) Takeoff time window assignment
32
1

Block-out timeassignment

19:15b) Predicted takeoff demand per 5 minutes

1Takeoff timewindow
assignment

19:00… 18:4554368 11 14 16 18 19
7 10 13 15 1720 22
9 12
21
19:00
19:15
19:30 … time13

ENRI Int. Workshop on ATM/CNS (EIWAC2013) 19-21FEB2013

Baseline scenario
Derived from observation of actual operation– Block-out/ -in time and gate
– Takeoff / landing time and runway
Hourly traffic volume80

arr22

Arr., B
arr23 D
Arr.,
Dep.,
dep16LC
Dep., A

number of flights

7060

dep16R

5040

Through the day
Dep.: 504 flights
Arr.: 525 flights

30
20100678910111213

14

15

time (JST)161718192021

2214

ENRI Int. Workshop on ATM/CNS (EIWAC2013) 19-21FEB2013

Modified scenario
94 departures were assigned block-out delay

Number of departures withdelayed block-out

14

7for 16L: t_REQ moved
Delay-assigned
Dep., C-RWY
for 16R: t_REQ moved
Delay-assigned
Dep., A-RWY
Avg.averageof assigned[min]of assigneddelay
wait

1210658463422100678910 11 12

13 14 15time (JST)16 17 18 19

Average of assigned delay [min]– Sum of delay: 249 min.
– Many for congested period in the evening

20 21 2215

ENRI Int. Workshop on ATM/CNS (EIWAC2013) 19-21FEB2013

Simulation result
Departurescontinually
comingQueue

Departure
ArrivalReduced
queue

RWY16R

Baseline scenario

Modified scenario

Queue reduction in congested period (19:30 JST)16

ENRI Int. Workshop on ATM/CNS (EIWAC2013) 19-21FEB2013
Performance index 1.

Reduction of taxiing time
How to measure– Comparing taxiing/queuing time between thesimulation result of baseline and modified scenario
Baseline
Scenario

Taxiing time
DEP003DEP002
DEP001
Queuing time

ModifiedScenario

DEP003DEP002
DEP001
Block-outJoin queue

TakeoffTime17

ENRI Int. Workshop on ATM/CNS (EIWAC2013) 19-21FEB2013
Performance index 1.

Reduction of taxiing time
Significant reduction in the evening– Through the day: total 2.12% (133 min.) reduction
for departure taxiing time
Decrease in departures' taxiing
time and queueing time [min]55
50

decrease in taxiing time45

decrease in queuing time

40
35
30
25
20
151050-5-106789101112131415time (JST)1617181920212218

ENRI Int. Workshop on ATM/CNS (EIWAC2013) 19-21FEB2013
Performance index 2.

Guarantee of takeoff time
How to measure– Punctuality: takeoff within the assigned takeoff
time window
Takeoff

5 minutes

Too early

Time
Assigned window
Takeoff

On timeTime
Assigned window
Takeoff

Too late

Time
Assigned window

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ENRI Int. Workshop on ATM/CNS (EIWAC2013) 19-21FEB2013
Performance index 2.

Guarantee of takeoff time
63.3% of departures took off within assigned
time window
Too earlyOn time
Too late
9080

Number of departures

70
60
5092 acft.
(18.2%)

319 acft.
(63.3%)-5 -4 -3 -2 -1

093 acft.
(18.5%)

4030
20
10012345678

9 10 11 12 13 14 15+

Difference b/w planned and resulting takeoff time [min]20

ENRI Int. Workshop on ATM/CNS (EIWAC2013) 19-21FEB2013

Discussion
18.2% took off slightly earlier than assigned
window (up to 4 min., mostly within 2 minutes)– Due to rough assumption on runway capacity
Sometimes #dep. + #arr. > 3

18.5% took off later than assigned window– In some cases, large deviation from assigned window
Though, takeoff times are same as baseline results– Due to unmodeled congestion factor
Congestion at aprons

These may be solved by detailed modeling21

ENRI Int. Workshop on ATM/CNS (EIWAC2013) 19-21FEB2013

Conclusions
Traffic management method suitable forHaneda airport– Departure taxi schedulingGood performance obtained– Reduction in departure taxi time : 2.12%– Guarantee on takeoff time : 63.3%

Problems to be solved– More precise forecast of runway capacity– Taxi time prediction method considering
apron congestion

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ENRI Int. Workshop on ATM/CNS (EIWAC2013) 19-21FEB2013

Acknowledgement
The authors express special thanks tothe Japanese Civil Aviation Bureau (JCAB)of the Ministry of Land, Infrastructure,
Transport and Tourism (MLITT)
for providing the source data.
and especially…

Thank you for your attention!
i-yamada

enri.go.jp
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ENRI Int. Workshop on ATM/CNS (EIWAC2013) 19-21FEB2013

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ENRI Int. Workshop on ATM/CNS (EIWAC2013) 19-21FEB2013

BACKUP SLIDES

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ENRI Int. Workshop on ATM/CNS (EIWAC2013) 19-21FEB2013

Motivation
CARATS says…
– “Bottlenecks at congested airports
and airspaces in the Greater
Tokyo Metropolitan area, etc.
must be eliminated”

Many literatures reporteffectiveness of Airport CDM– How will Airport CDM work atHaneda airport?
Reference: JCAB, “Long-term Vision for the Future Air Traffic Systems”, 2010.
http://www.mlit.go.jp/common/000128185.pdf

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ENRI Int. Workshop on ATM/CNS (EIWAC2013) 19-21FEB2013

Our research topics
Technical arguments on traffic management atHaneda airport– Post-operation data processing– Surface traffic flow analysis
Identification of congested area
Queue analysis– Airport surface movement simulator– Traffic management methods– Evaluation methods for traffic management
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ENRI Int. Workshop on ATM/CNS (EIWAC2013) 19-21FEB2013

Traffic management algorithm 1/2
Arrivals assumed as independent movement– Landing time assumed as fixedenabling takeoff capacity prospect

Time management for departures– Predict takeoff demand at runway from initialplanning of departing gate
– Detect excess demand compared to the prospect oftakeoff capacity– Assign wait at gate for excess demand
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ENRI Int. Workshop on ATM/CNS (EIWAC2013) 19-21FEB2013

Congestion at apron
Departure’s taxiing route is blocked by arrivals

headway
blocked29