8 th USA/Europe Air Traffic Management R&D Seminar. US/Europe comparison of ATM-related operational performance. June 30, 2009 Napa Valley, California

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1 8 th USA/Europe Air Traffic Management R&D Seminar US/Europe comparison of ATM-related operational performance June 30, 2009 Napa Valley, California

2 Objective & Scope OBJECTIVES Provide a high-level comparison of operational performance between the US and Europe Air Navigation systems. Initial focus on the development of a set of comparable performance for high level comparisons between countries and world regions. SCOPE Predictability and Efficiency of operations Continental airspace (Oceanic and Alaska excluded) Focus on data subset (traffic from/to top 34 airports) due to better data quality (OEP airports) and comparability (general aviation). Commercial IFR flights NOT in SCOPE Safety, Cost effectiveness, Capacity Trade-offs and other performance affecting factors (weather, etc.) 2

3 Assessing Performance ANSP Performance Measures RADAR Databases Airline Delay/Performance Databases Simulation Models Procedures Airspace Redesign System-wide Models Airlines Flight Planning, Fuel Requirements Flight Trials Aspire Louisville CDA 3

4 Overview Comparing USA & Europe Calendar Year 2008 Europe[1] USA[2] Difference Geographic Area (million km 2 ) % Number of en-route Air Navigation Service Providers 38 1 Number of Air Traffic Controllers % Total staff % Controlled flights (Instrumental flight rules IFR) (million) % Share of General Air Traffic 4% 23% x5.5 Flight hours controlled (million) % Average length of flight (within region) 524 NM 497 NM -5% Nr. of en-route centers % En-route sectors at maximum configuration % Nr. of airports with ATC services [3] (280) +12% Of which are slot controlled > 73 4 Source Eurocontrol FAA/ATO [1] Eurocontrol States plus the Estonia and Latvia, but excluding oceanic areas and Canary Islands. [2] Area, flight hours and center count refers to CONUS only. The term US CONUS refers to the 48 contiguous States located on the North American continent south of the border with Canada, plus the District of Columbia, excluding Alaska, Hawaii and oceanic areas. [3] All facilities of which 280 are FAA staffed and 223 contract towers. 4

5 Airspace Density Comparison (CONUS & European Centers) *Note due to Mercator projection, northern areas appear larger Density (flight Hr per Sq.Km) < 1 < 2 < 3 < 4 < 5 >= 5 Actual sizes are comparable (USA 10.4 vs Europe 11.5 M km 2 ) Relative density (flight hours per km 2 ) is 1.2 in Europe and 2.4 in US 5

6 Air traffic growth in the US and in Europe (IFR flights) 8% 6% 4% 2% 0% -2% -4% USA Europe -6% Until 2004, growth rates evolved in similar ways Notable decoupling since

7 On-time performance in the US and in Europe 90% 88% 86% 84% 82% 80% 78% 76% 74% On-time performance compared to schedule (flights to/from the 34 main airports) Intra-Europe 90% 88% 86% 84% 82% 80% 78% 76% 74% US (conus) Arrivals/ departures delayed by more than 15 minutes versus schedule 72% 70% Source: E-CODA 72% 70% Source: ASQP data Departures (<=15min.) Arrivals (<=15min.) Similar pattern in US and Europe with a comparable level of arrival on time performance; The gap between departure and arrival punctuality is significant in the US and quasi nil in Europe suggesting differences in flow management strategies 7

8 Airline Scheduling: Evolution of block times Evolution of Scheduled Block Times (flights to/from 34 main airports) 4 Europe 4 US (conus) 3 3 minutes Scheduled block times compared to the long term average at city pair level Jan-00 Jan-01 Jan-02 Jan-03 Jan-04 Jan-05 Jan-06 Jan-07 Jan-08 Jan-00 Jan-01 Jan-02 Jan-03 Jan-04 Jan-05 Jan-06 Jan-07 Jan-08 Source: FAA/PRU Europe: Block times remain relatively stable (left side) US: In addition to decreasing on time performance (previous slide), there is a clear increase in scheduled block times (right side) Seasonal effects are visible in the US and in Europe 8

9 Efficiency: Trends in the duration of flight phases minutes Trends in the duration of flight phases (flights to/from main 34 airports) 6 DEPARTURE TIMES TX-OUT TIMES 5 AIRBORNE TIMES 4 TX-IN TIMES TOTAL Actual times are compared to the long term average for each city pair Jan-03 Jul-03 Jan-04 Jul-04 Jan-05 EUROPE Jul-05 Jan-06 Jul-06 Jan-07 Jul-07 Jan-08 Jul Jan-03 Jul-03 Jan-04 Jul-04 Jan-05 Jul-05 Jan-06 US Jul-06 Jan-07 Jul-07 Jan-08 Jul-08 Data Source: CODA/ FAA Europe: performance is driven by departure delays with only very small changes in the gate-to-gate phase. US: in addition to a deterioration of departure times, there is a clear increase in average taxi times and airborne times. 9

10 Schedule Growth Shifts Delays Traffic Change Delayed Flights Change in Operations since % 8% 6% 4% 2% 0% -2% -4% -6% -8% -10% -12% OEP Delays per Thousand Operations EWR,JFK,LGA,PHL Down 9% Compared to 2000 Up 8% Compared to 2000 October-July 10

11 Predictability: Variability of flight phases Variability of flight phases (flights to/from 34 main airports) US - (80th 20th)/2 EU - (80th 20th)/2 12 minutes Departure time (compared to schedule) Taxi-out + holding Flight time (cruising + terminal) Taxi-in + waiting for the gate Arrrival time (compared to schedule) Gate-to-gate phase Source: FAA/PRC Predictability is measured in from the single flight perspective (i.e. airline view) as the difference between the 80th and the 20th percentile for each flight phase. Arrival predictability is mainly driven by departure predictability. With the exception of taxi-in, variability for all flight phases is higher in the US. 11

12 What We are Measuring Today (w/ Large Data Sets) FAA/ATO and PRU both establishing consistent measures IFR flights To/from Main 34 airports DEPARTURE ANS-related Holding at the Gate (ATFM/ EDCT) Taxi-out efficiency GATE-to-GATE En-route Flight efficiency Efficiency In last 100NM Taxi-in efficiency IFR flights To/from Main 34 airports Feb 15th h01-23h59 Continuous Descent Arrival 100 nm 40 nm Standard Arrival 12

13 Efficiency: ANS-related departure delays DEPARTURE ANS-related Holding at the Gate (ATFM/ EDCT) Taxi-out efficiency GATE-to-GATE En-route Flight efficiency Efficiency In last 100NM 2007 En-route related (EDCT/ATFM) Airport related (EDCT/ATFM) delay per delayed flight (min.) delay per flight (min.) % of flights delayed delay per delayed flight (min.) delay per flight (min.) % of flights delayed IFR flights (M) US % % Europe % % US: En-route delays are much lower per flight, but the delay per delayed flight is significantly higher; Europe: Higher share of flights affected (than US) but with a lower average delay. In the US, ground delays (EDCT) are used when other options are not sufficient, whereas, in Europe ground delays (ATFM) are the main ATM tool for balancing demand with capacity 13

14 Excess time in the taxi out phase Average excess time in the taxi out phase (Top 20 in terms of annual movements in 2007 are shown) DEPARTURE ANS-related Holding at the Gate (ATFM/ EDCT) Europe Top 34 Average (3.7 min.) Taxi-out efficiency GATE-to-GATE En-route Flight efficiency Efficiency In last 100NM minutes per departure London (LHR) Rome (FCO) London (LGW) Frankfurt (FRA) Paris (CDG) Madrid (MAD) Barcelona (BCN) Munich (MUC) Istanbul (IST) Amsterdam (AMS) Milan (MXP) Dusseldorf (DUS) Manchester (MAN) Vienna (VIE) Zurich (ZRH) Oslo (OSL) Copenhagen (CPH) Paris (ORY) Brussels (BRU) Stockholm (ARN) US OEP 34 Average (6.8 min.) New York (JFK) Newark (EWR) New York (LGA) Philadelphia (PHL) Atlanta (ATL) Chicago (ORD) Minneapolis (MSP) Detroit (DTW) Boston (BOS) Charlotte (CLT) Salt Lake City (SLC) Las Vegas (LAS) Houston (IAH) Phoenix (PHX) Denver (DEN) Washington (IAD) San Francisco Dallas (DFW) Los Angeles Orlando (MCO) Source: FAA/ PRC analysis/ CODA/ CFMU Excess times in the taxi out phase are higher in the US For the US, excess times also include delays due to local en-route departure and miles in trail restrictions..

15 En-route flight Efficiency: Approach DEPARTURE ANS-related Holding at the Gate (ATFM/ EDCT) Taxi-out efficiency GATE-to-GATE En-route Flight efficiency Efficiency In last 100NM Airport B Actual route (A) G D A Direct Course (D) Direct route extension TMA interface En-route extension Focus on horizontal flight efficiency Distance based approach Airport A 40 NM Great Circle (G) Indicator is the difference between the length of the actual trajectory (A) and the Great Circle Distance (G) between the departure and arrival terminal areas. Direct route extension is measured as the difference between the actual route (A) and the direct course between the TMA entry points (D). This difference is an ideal (and unachievable) situation where each aircraft would be alone in the sky and not subject to any constraints (i.e. safety, capacity). 15

16 Flight efficiency: Direct Route Extension Direct route extension (%) % of all flights 5.0% 4.5% 4.0% 3.5% 3.0% 2.5% 2.0% 1.5% 1.0% 0.5% 0.0% 40% 30% 20% 10% 0% Direct en-route extension ((A-D)/G) (flights to/from the 34 main airports 2007) NM NM NM NM NM >1000 NM Great Circle Distance between 40NM circles (D40-A40) Europe USA DEPARTURE ANS-related Holding at the Gate (ATFM/ EDCT) European top 34 average (4.0%) US OEP 34 average (2.9%) NM NM NM NM NM >1000 NM Direct route extension is approximately 1% lower in the US Taxi-out efficiency US: Miles in trail restrictions are passed back from constrained airports Europe: Fragmentation of airspace, location of military airspace GATE-to-GATE En-route Flight efficiency Efficiency In last 100NM 16

17 Impact of Military Airspace SW of Frankfurt DEPARTURE ANS-related Holding at the Gate (ATFM/ EDCT) Taxi-out efficiency GATE-to-GATE En-route Flight efficiency Efficiency In last 100NM Military airspace is a significant driver of excess distance Area southeast of Frankfurt is a major contributor Adjoining French Military airspace further increases problem 17

18 Seasonal Effects of Excess Distance Peak in 5 Month period 4/1-9/ Excess Distance (nm) /23/ /5/2001 3/20/2003 8/1/ /14/2005 4/28/

19 IAD to FLL 19

20 Efficiency: Excess time in the last 100NM Direction of Flight Actual Route Arrival Fix Arrival Airport Notional Optimal Route 2.5% x 40 nmi Time based measure Captures type of A/C ARC Entry point and runway configuration Nominal derived from 20th percentile Excess time above nominal for each category 100 nmi 20

21 Excess time within the last 100NM DEPARTURE ANS-related Holding at the Gate (ATFM/ EDCT) Taxi-out efficiency GATE-to-GATE En-route Flight efficiency Efficiency In last 100NM Average Excess Minutes within the last 100NM miles (only top 20 airports in terms of movement 2007 are shown) Europe Top 34 Average (3.2 min.) London (LHR) Frankfurt (FRA) Vienna (VIE) Madrid (MAD) London (LGW) Munich (MUC) Zurich (ZRH) Rome (FCO) Dusseldorf (DUS) Milan (MXP) Manchester (MAN) Barcelona (BCN) Paris (ORY) Paris (CDG) Oslo (OSL) Brussels (BRU) Copenhagen (CPH) Amsterdam (AMS) Istanbul (IST) Stockholm (ARN) minutes Source: FAA/ PRC analysis US OEP 34 Average (2.5 min.) Newark (EWR) Philadelphia (PHL) New York (JFK) New York (LGA) Charlotte (CLT) Detroit (DTW) Atlanta (ATL) Chicago (ORD) Boston (BOS) Washington (IAD) Minneapolis (MSP) San Francisco Orlando (MCO) Denver (DEN) Phoenix (PHX) Dallas (DFW) Las Vegas (LAS) Los Angeles Houston (IAH) Salt Lake City (SLC) minutes Average excess time for main 34 airports is higher in Europe Mainly driven by London Heathrow (LHR) which is clearly an outlier Performance at LHR is consistent with the 10 minute average delay criteria agreed by the airport scheduling committee. 21

22 Vertical Inefficiency - Continuous Descent Arrival CDA is an arrival procedure designed to eliminate level segments flown below cruise altitude, thus minimizing fuel burn, emissions and noise. Continuous Descent Arrival In a CDA, these level segments would be flown at cruise altitude Standard Arrival 22

23 Estimated total benefit pool Estimated excess time on flights to/from the main 34 airports (2007) TIME per flight (minutes) EUR Predictability Gate/ departure en-route-related Low holdings airport-related Low Taxi-out phase Medium Horizontal en-route flight efficiency High Terminal areas (ASMA/TMA) Medium Total estimated excess time per flight US The benefit pool represents a theoretical optimum. Safety and capacity constraints limit the practicality of ever fully recovering these inefficiencies Similar total estimated excess times in US and Europe but with differences in the distribution along the phase of flight. Inefficiencies have a different impact (fuel burn, time) on airspace users, depending on the phase of flight (airborne vs. ground) and the level of predictability (strategic vs. tactical). 23

24 Research Issues Improved Perspective On Benchmark Times Optimized Aircraft Trajectories Account for Necessary System Constraints Airline Perspective Predictability Address Limitations of Performance Data What Inefficiency is Purely Attributed to ATM? 24

25 Conclusions High value in global comparisons and benchmarking in order to drive performance and identify best practice; Arrival punctuality is similar in the US and in Europe, albeit with a higher level of variability in the US. Overall, the estimated average excess time in the US and Europe appear to be similar, but with notable differences in the distribution along the phase of flight. Inefficiencies have a different impact (fuel burn, time) on airspace users, depending on the phase of flight (airborne vs. ground) and the level of predictability (strategic vs. tactical). Further work is needed to assess the impact of efficiency and predictability on airspace users. A more comprehensive comparison of service performance would also need to address Safety, Capacity and other performance affecting factors such as weather and governance. 25

26 ICAO/SESAR Key Performance Areas fall into 3 major groups KPAs FAA has similar Focus Areas Mapping to these KPAs 26

27 Aspire Flight Test Flight Demonstration from New Zealand to SFO Publicized Benefit of ~4% Mix of ATM & Airline Procedures Airline Procedures Max Takeoff Thrust Slower Speeds Delayed Flap Ground Fueling/Reduced APU Not clear if ATM Benefit already realized User Preferred Routes Optimum Altitude 27

28 ASPIRE Flight Test FAA/ATO Indicator Aspire Direct Flight Indicator 1.6%-3.0% 1.4%-1.7% TMA w/vertical 3.3% 0.7% Ground Taxi Delay 1.6%-1.9% 0.07% ATM ASPIRE 6.5%-8.2% 2.42% Phase 1 Airline Procedure 0.44% Phase 2 & 4 Airline Procedure 0.41% Phase 3 Optimum Altitude 0.46% Phase 3 Slower Speeds 0.31% Non-ATM/RVSM 1.61% Total ASPIRE 4.03% 28

29 SAN to JFK Flights for July 2007 Great Circle Distance: 2120 nmi Total Average Excess Distance: 183 nmi Percent Excess Distance over Great Circle: 8.6% Average excess distance per stage: First 40 nmi: 27 nmi 40 to 40 nmi circles: 97 nmi Last 40 nmi: 59 nmi 29

30 SAN to JFK: Actuals July 2007 Actual trajectories (blue) 100 nmi circle Around SAN Great Circle Trajectory (black) 100 nmi circle Around JFK 30

31 SAN to JFK: Actuals and Wind Optimal July 2007 Wind optimal trajectories (purple) 31

32 SAN to JFK: Example JBU184 on July 27, 2007 Actual Route Multiple holding circles. Excess time probably resulting from weather or congestion at JFK. Wind Optimal Route Difference between estimated times is 50.5 minutes. 32

33 ASPM Total Delay - FY ,418,450 Domestic Arrivals Taxi In Delay, 8% 1.64 Min Airborne Delay, 6% 1.14 Min Minutes Average Delay Taxi Out Delay, 23% 4.5 Min Gate Delay, 63% 12.6 Min 33

34 FY2007 DOT Form 41 and Model Data Domestic Commercial Flights 10,843,220 Actual Fuel: Total (Gallons) 13,594,891,33 0 Actual Fuel: per Flight (Gallons) 1254 Actual Fuel: per Flight (kg) 3,875 34

35 SWF to FLL Number of Flights 846 Direct Flight Indicator Total (A-G) Direct Between TMA (A-D) 68.0 TMA Interface (G-D)

36 Boston (BOS) to Philadelphia (PHL) Flights DEPARTURE ANS-related Holding at the Gate (ATFM/ EDCT) Taxi-out efficiency GATE-to-GATE En-route Flight efficiency Efficiency In last 100NM July 2007 Great Circle Distance: 242 nmi Average Excess Distance: 102 nmi Percent Excess Distance over Great Circle: 42.1% Average excess distance per stage: First 40 nmi: 12 nmi 40 to 40 nmi circles: 63 nmi Last 40 nmi: 27 nmi 36

37 EDCT Delays (min) EDCT Delays (Flights-Thousands) En Route Driven Ground Delays (ATO) 1,800 1,500 En Route Delayed Flights 1, En Route Delays (min) 0 Oct-06 Nov-06 Dec-06 Jan-07 Feb-07 Mar-07 Apr-07 May-07 Jun-07 Jul-07 Aug-07 Sep-07

38 Excess Taxi Fuel Burn Calculation Methodology Calculate taxi-in/taxi-out delay from ASPM/ASQP -using actual taxi time and nominal taxi time from ASPM - Nominal Benchmark Time -Taxi-delay = actual time nominal time Derive excess fuel usage from taxi-in/taxi-out delay ICAO Emission Databank Excess fuel used in kg = taxi delay in minute * fuel burn kg/min Airline Assumptions on Fuel 38

39 FAA/ATO Delays Most En Route Delays during Convective Weather 9 Annual Ops Annual Delay Monthly Delay Jan-00 Jul-00 Jan-01 Jul-01 Jan-02 Jul-02 Jan-03 Jul-03 Jan-04 Jul-04 Jan-05 Jul-05 Jan-06 Jul-06 Jan-07 Jul-07 Annual Ops (Million) Avg. Total Delay 5 0

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