Uncertainty in Airport Planning Prof. Richard de Neufville

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Transcription:

Uncertainty in Airport Planning Prof. Richard de Neufville Istanbul Technical University Air Transportation Management M.Sc. Program Airport Planning and Airport Planning and Management Module 06 January 2017

Massive Uncertainty Objective: To present realistic context of forecasting exercise Topics Evidence Consequences

Causes of Uncertainty Underlying variability of phenomenon Difficulties in measurement or estimation Unforeseen or unpredictable circumstances Limits to valid measurement for example: behavioral patterns

Evidence 1. Simple Physical Systems 2. Overall Traffic 3. Local Traffic (Worse) 4. Other Operations

Percent of Occurrences Ratio of Real Costs to Estimated Costs for Airport Projects 15 Costs expressed in constant dollars Median ~= 1.25 10 5 0 0 0.5 1 1.5 2 2.5 Real/Estimated Cost Ratio

Ratio of Actual to Estimated Cost Cost Growth for Various Projects 3.0 2.5 2.0 1.5 1.0 0.5 0.0 DOD60 HWAY WATER BLDNG DOD50 ADHOC MAJOR ENRGY NASA NASA AVG St.Dev. CONST SAT m g

Ratio of Actual to Estimated Cost NASA Projects Cost Growth 3.5 3.0 2.5 2.0 1.5 1.0 0.5 0.0 HST GLL UARS GRO COBE MGL MOBS LSAT EUVE ERBE AVG St.Dev.

Domestic Revenue Passenger Miles (billions of RPMs) US Revenue Pax-Miles (RPM) 900 Domestic RPMs Projection vs. Reality 800 700 600 500 400 Historical Domestic RPMs Projected Domestic RPMs 300 200 100 0 1995 1997 1999 2001 2003 2005 2007 2009 2011 2013 2015 Seamus Bann and MIT Airline Data Project, Domestic Revenue Passenger Miles. http://web.mit.edu/airlinedata/www/2015%2012%20month%20documents/ Traffic%20and%20Capacity/Domestic/Domestic%20Revenue%20Passenger%20Miles.htm

Jet Fuel Consumed (billions of gallons) Jet Fuel Use in US 30 Commercial Jet Fuel Consumption Projection vs. Reality 25 20 15 Historical Commercial Jet Fuel Consumption Projected Commercial Jet Fuel Consumption 10 5 0 1995 1997 1999 2001 2003 2005 2007 2009 2011 2013 2015 Source: Seamus Bann and MIT Airline Data Project, Total Gallons of Fuel. http://web.mit.edu/airlinedata/www/2015%2012%20month%20documents/ Expense%20Related/Fuel/Total%20Gallons%20of%20Fuel.htm

Total Fuel Consumed (Millions of Gallons) US Consumption of Aviation Fuel 40000 35000 30000 25000 20000 15000 10000 5000 0 1990 1995 2000 2005 2010 2015 2020 2025 Year 2000 Forecast 2001 Forecast 2002 Forecast 2003 Forecast 2004 Forecast 2005 Forecast 2006 Forecast 2007 Forecast 2008 Forecast 2009 Forecast 2010 Forecast Actual Values http://www.faa.gov/about/office_org/headquarters_offices/apl/aviation_forecasts/aer ospace_forecasts/ Per Morgan Edwards 2011

Cumulative Distribution Results of a 2004 study Errors in 5 year TAF 1.2 1 0.8 0.6 0.4 0.2 0 0 10 20 30 40 50 Percent error (Absolute value) Adapted from: Terminal Area Forecast (TAF) Accuracy Assessment Results Jerome Friedman, MITRE CAASD, Sept. 30, 2004

Fregquency of Error (%) Results of a 2004 study Errors in 5 year TAF 20 15 10 5 Note: Average error ~ 11% 0 0 3 7 10 13 17 20 23 27 30 33 36 40 Percent Error (Absolute value) Adapted from: Terminal Area Forecast (TAF) Accuracy Assessment Results Jerome Friedman, MITRE CAASD. Study dated Sept. 30, 2004, but data until 2000. Deliberate omission of 2001, 2002 when traffic dropped enormously

Error Data from U.S Source: MITRE CAASD and FAA City 5 YEAR FORECAST FROM / TO 92 93 94 95 97 98 99 2000 ATL 10.8-10 -15.5-13.3 BOS -0.8-2.1-0.2 8.9 BWI 27.4 6.3-5.8 7.5 CLE -13.4-14.6-17.5-13.3 CLT 7.8 15.8 10.9 18.1 CVG -0.9-4.3-14.5-9.5 DCA 7.5 13.8 2.7-5.1 DEN 18 19.6 19.9 5.5 DFW 2.6-3.2 7.8 14.2 DTW -13.2-6.5-8.6 3.1 EWR -12.2-5.9-0.1 5 FLL 17.2 3.4-3.8-11.6 HNL 28.2 40.9 23 14.9 IAD -6.4-9.5-41.4-41.2 IAH -8.1-12.3-8.9-25.4 JFK -0.9 6.2 11.7 3.8

Error Data from U.S Source: MITRE CAASD and FAA City 5 YEAR FORECAST FROM / TO 92 93 94 95 97 98 99 2000 LAS -5.1-2.2-10.4 8.5 LAX 2.2-1.6-1.4 0.6 LGA 7.7 3.9-3.2-4.8 MCO 15.9 15.1 18.6 14.9 MDW 33.9-21.3-32.9-5.2 MEM 9.1 16.3 10 4.7 MIA 3.9 3.8 13.1 21.5 MSP -5.4 0.4 5.6 0 ORD -6.8-5.1-3.4 2 PDX -3.9-12.2-9.5 3.5 PHL -3.2-7.2-4.2 0.1 PHX 6.1 6 4.1-2.8 PIT 9.4 9.9 8.2 6.6 SAN 21.6 20 15.6 20.6 SEA 6.3-0.8-15.3-9.3 SFO 25.7 22.5 17.4 10.7 SLC -6.7-0.2-0.3 9.8 STL -7.4-1.3-3.3 4.9 TPA 16.5 12.4 6.9 5.6

Locid City Airport Name Preliminary CY08 Total Enplanements Forecast 2004 TAF in thousands % Difference CVG Cincinnati Cincinnati/Northern Kentucky International 6,488,422 13193-103.3 IAD Washington Washington Dulles International 11,287,621 15861-40.5 MDW Chicago Chicago Midway International 8,019,338 10714-33.6 MSP Minneapolis St. Paul Minneapolis-St Paul International/Wold-Chamberlain 16,352,653 21361-30.6 BWI Baltimore Washington Baltimore/Washington International Thurgood Marshal 10,206,399 13135-28.7 HNL Honolulu Honolulu International 9,000,365 11483-27.6 DTW Detroit Detroit Metropolitan Wayne County 16,993,820 20183-18.8 LAX Los Angeles Los Angeles International 28,612,013 33628-17.5 ORD Chicago Chicago O'Hare International 33,668,545 38760-15.1 TPA Tampa Tampa International 8,869,806 10182-14.8 BOS Boston General Edward Lawrence Logan International 12,784,965 14658-14.7 LGA New York La Guardia 11,549,790 13225-14.5 PHL Philadelphia Philadelphia International 15,577,122 17817-14.4 PHX Phoenix Phoenix Sky Harbor International 19,433,827 22175-14.1 FLL Fort Lauderdale Fort Lauderdale/Hollywood International 11,018,382 12557-14.0 SLC Salt Lake City Salt Lake City International 9,889,030 11180-13.1 MCO Orlando Orlando International 17,271,885 19192-11.1 STL St. Louis Lambert-St Louis International 6,644,199 7359-10.8 ATL Atlanta Hartsfield - Jackson Atlanta International 43,737,608 47130-7.8 DFW Dallas/Ft.Worth Dallas/Fort Worth International 27,206,541 29202-7.3 LAS Las Vegas McCarran International 21,011,949 22424-6.7 SAN San Diego San Diego International 9,007,602 9437-4.8 SFO San Francisco San Francisco International 18,101,502 18496-2.2 IAH Houston George Bush Intercontinental/Houston 19,850,397 20070-1.1 EWR New York Newark Liberty International 17,578,856 17604-0.1 PDX Portland Portland International 7,073,767 6956 1.7 SEA Seattle Seattle-Tacoma International 15,815,133 15456 2.3 DCA Washington Ronald Reagan Washington National 8,692,131 8336 4.1 JFK New York John F Kennedy International 23,601,779 22306 5.5 DEN Denver Denver International 24,266,328 22817 6.0 MIA Miami Miami International 16,369,998 15369 6.1 CLT Charlotte Charlotte/Douglas International 17,271,119 14678 15.0 Actual 2008 traffic compared to that forecast in 2004 TAF Source: US FAA Sum -426.5 Average -13.3 Sum Absolute 507.7 Average Absolute 15.9

Actual vs. Forecast 10 years prior Source: FAA Aerospace Forecast FY 2006-2017 Domestic Commercial Emplanements Year being forecast Actual vs. Forecast 1995 11.4 1996 12.2 1997 17.4 1998 14.9 1999 9.9 2000 5.5 2001 4.7 2002 14.5 2003 12.5 2004 20.0 2005 13.9 Median and Average 12.5 Note: These are aggregate data, in which greater local variations tend to cancel each other out

Older FAA Forecasts vs. Actual Data (% Difference) Forecast Year For Year Commercial Enplnmnts. Revenue Pax. Miles Hrs. General Aviation GA Ops at FAA Towers Tot. Ops at FAA Towers 1959 1964 (1.30) (6.50) (0.60) 4.60 9.70 1960 1965 (9.50) (9.70) (1.20) (27.80) (21.60) 1961 1966 (27.50) (26.00) (15.30) (37.70) (28.90) 1962 1967 (32.10) (31.40) (23.60) (34.70) (27.30) 1963 1968 (41.30) (41.30) * (38.40) (32.50) 1964 1969 (31.40) (33.60) (23.50) (27.30) (24.90) 1965 1970 (14.10) (19.80) (16.30) (2.60) (5.20) 1966 1971 9.40 0.50 (1.60) 53.70 42.20 1967 1972 23.60 13.00 9.10 72.50 54.90 1968 1973 23.90 15.90 7.40 78.30 58.40 1969 1974 21.10 21.20 4.60 53.60 42.40 1970 1975 26.30 33.00 (0.60) 80.90 25.90 1971 1976 19.00 28.60 (0.60) 42.90 22.90 1972 1977 22.30 33.70 (6.80) 36.90 4.50 1973 1978 14.00 18.30 (10.40) 14.80 8.80 1974 1979 (9.70) (7.40) (13.70) 11.80 9.40 1975 1980 (10.60) (17.30) (0.20) 34.60 25.70 1976 1981 4.30 (1.80) 15.70 41.30 32.10 Review of the FAA 1982 National Airspace System Plan

Forecast vs Actual International Pax in Sydney Forecast For Year Source of Forecast, in Year Consultant Regional Study National Ministry 1974 1978 1983 1980 3.77 2.98-3.46 1985 7.4 3.87-4.34 2.674-3.047 1990 9.8 4.71-5.51 2.762-3.751 2000 projected 12.0 6.27-8.66 2.938-5.159 2000 actual 10 Compare reported 4 significant figures with Failure to get the first one correct!

Forecast vs. Actual International Pax in Japan Forecast Passengers (million) Percent Error For Done In Actual Forecast Difference/Actual 1980 1970 12.1 20.0 65 1985 1975 17.6 27.0 53 1990 1980 31.0 39.5 27 1995 1985 43.6 37.9 (13)

10,000 ton Forecast vs. Actual International Pax to Japan 450,000 400,000 350,000 300,000 250,000 200,000 150,000 100,000 50,000 0 1955 1960 1965 1970 1975 1980 1985 1990 1995 2000 Year Actual Forecast

Notice the Pattern! Forecasting is an exercise in projecting past into future like steering car by looking into rear view mirror! Past low growth => under estimation Past high growth => over estimation Almost never right!

We don t tend to update properly See the following slides We are slow to adjust to new experience Wishful thinking?

NUMBER OF AIRCRAFT ACTIVE GENERAL AVIATION AIRCRAFT 1980 FORECAST 400 ACTUAL 80 FCST. 300 200 100 0 70 72 74 76 78 80 82 84 86 88 90

NUMBER OF AIRCRAFT ACTIVE GENERAL AVIATION AIRCRAFT 1985 FORECAST 400 ACTUAL 80 FCST. 85 FCST. 300 200 100 0 70 72 74 76 78 80 82 84 86 88 90 92 94

NUMBER OF AIRCRAFT ACTIVE GENERAL AVIATION AIRCRAFT 1990 FORECAST 400 ACTUAL 80 FCST. 85 FCST. 90 FCST. 300 200 100 0 70 74 78 82 86 90 94 98

NUMBER OF AIRCRAFT ACTIVE GENERAL AVIATION AIRCRAFT 1998 FORECAST 400 ACTUAL 80 FCST. 85 FCST. 90 FCST. 98 FCST. 300 200 100 0 70 74 78 82 86 90 94 98 02 06

Terminal Area Forecasts vs Actual Porcupine Diagram

Projected vs Actual US Electric Power Use

OK, we re slow but? Many examples of tendency to not adjust Is it just inability to learn? What else might it be? Budget imperatives a possibility

Summary and Recommendations Summary Forecast Errors have been large Likely to continue Recommendations: Expensive Forecasting is cost-ineffective Use general trends...with large ranges Flexible Approach to Planning!!! If we don t the future, should anticipate and prepare for many possibilities.