sandro poster
DESCRIPTION
CURA researcher Sandro de Almeida has begun working with a real flight track dataset, captured by automatic dependent surveillance – broadcast (ADS-B) antennae. By analyzing the data provided by this cooperative surveillance technology, CURA can understand how flights are being operated by airlines and eventually propose new flight strategies that could lead to improved fuel efficiency and reduced carbon emissions.TRANSCRIPT
Selecting the appropriate type of aircraft for a set of routes is an important task for
airlines in order to save fuel and reduce CO2 emissions
I. Introduction
Data acquisition: 81 millions of waypoints captured by worldwide ASD-B antennas
Diff (%) = [(WPD / GCD) – 1] x 100
Data analysis – Dimensions & Metrics MetricsFlight phase Total
Climb Cruise Descent Origin-Destin
Avg. GCD 65.54 NM (22.54%) 148.41 NM (51.03%) 76.87 NM (26.43%) 290.81 NM (100%)
Avg. WPD 72.34 NM (22.67%) 150.60 NM (47.20%) 96.15 NM (30.13%) 319.08 NM (100%)
Avg. Diff (%) 10.38% 1.47% 25.09% 12.32%
Standard dev. 4.86% 1.43% 20.46% 5.34%
Equipment
Flights Distribution: Great Circle Distance vs Waypoint Distance
Averages
Big data processing
Flight paths take their biggest deviation in the climb and descent phases — nearly 10% and 25% respectively — compared with the cruise phase (which tends
to be much more predictable). The results also show that phase distances are not linear in respect to total flight distances for trips below 500 nautical miles.
The aircraft models E175 and B75 take more deviation in the climb stage while RJ1H tend to has more deviation in the descent phase. The U.S. flights operated
by AirTran Airways airline and the flights departing from BOS, JFK, MIA and SNA airports tend to have more deviation in the climb stage (>20%).
Future work will link this analysis with an accurate fuel burn estimating model in order to analyze flight networks and their costs.
Acknowledgement: (I) Center for Urban and Regional Analysis and The Ohio State University (II) CAPES (Agency of Brazilian Ministry of Education) –Program Science Without Borders (III) PlaneFinder.net - Live Flight Status Tracker
Aircraft efficiency varies across routes stages.
It is potentially useful to understand how aircraft consume fuel across different flight
distance ranges.
Objective: this work analyzes phase distances of worldwide flights with distance
below 1000 NM.
V. Conclusion
III. Results
Big Data Analysis of Flight Phases Distance Using Multi-Agent SystemsSandro Jerônimo de Almeida, Morton E. O’ Kelly & Ricardo Poley Martins Ferreira
Data collected by feeders of PlaneFinder.net in September 2013
Data filter and transformation: waypoints were transformed in approx. 1 MM flights
38,341 flights are complete (exists at least 1 waypoint at each 20 km in the route)
For each flight the median filter was used to remove noise in waypoints (lat, long, alt).
A Multi-agent system (MAS) was used to reproduce/simulate the complete flights
The MAS adopts a flight phases classification algorithm based on ICAO standards
For each flight phase were computed the great circle distance (GCD) and the sum
of the distances between the waypoints of the route (WPD)
Dimension 1: climb (ascent), cruise and descent flight phases
Dimension 2: distance rate, equipment model and U.S. airline and airports
Metrics: GCD, WPD and the percentage difference between GDC and WPD (Diff %)
II. Methodology
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Great Circle Distance (NM)
Descent stage
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Total Trip Distance (NM)
Flight Phase Distance
Taxi out + Take Off + Climb Cruise Descent + Landing + Taxi in
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Total Trip Distance (NM)
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Total Trip Distance (NM)
Taxi out + Take off + Climb Cruise Descent + Landing + Taxi out Total
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Taxi out + Take off + Climb Cruise Descent +Landing + Taxi in
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AUS BOS BWI DCA DEN DFW FLL IAH JFK LAS LAX LGA LGB MCO MIA OAK ORD SAN SFO SLC SMF SNA
Dif
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AirTranAirways
AmericanAirlines
Delta AirLines
FrontierAirlines
JetBlueAirways
SouthwestAirlines
Spirit Airlines UnitedAirlines
United ParcelService
VirginAmerica
WestJet
Dif
fere
nce
(%
) G
CD
an
d W
PD
A306
A318A319
A320A321
A388
AT76
B733
B734B735
B736 B737B738
B739
B752B753
B763B788
E175
E190
E195
F100
F70
RJ1H
RJ85
0.00%
10.00%
20.00%
30.00%
40.00%
50.00%
60.00%
70.00%
0.00% 5.00% 10.00% 15.00% 20.00% 25.00%
Dif
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) o
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Stag
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Difference (%) on Climb Stage
Difference (%) between GCD and WPD on climb and descent phases
Deviation:
U.S. Airports and Airlines
Flights Phase Distance vs Total Trip Distance Diff (%) between GCD and WPD vs Total Trip Distance