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Airport Capacity Problem Southern California Transportation Alternatives LCDR Kirby and LT Burba

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Airport Capacity Problem. Southern California Transportation Alternatives LCDR Kirby and LT Burba. Introduction Southern California’s Airports are at Capacity Generally crowded airspace and crowded airports Model of major US airports - PowerPoint PPT Presentation

TRANSCRIPT

Page 1: Airport Capacity Problem

Airport Capacity Problem

Southern California Transportation Alternatives

LCDR Kirby and LT Burba

Page 2: Airport Capacity Problem

• Introduction• Southern California’s Airports are at Capacity• Generally crowded airspace and crowded

airports• Model of major US airports• Introduction of a High Speed Rail to reduce

strain on Southern California’s airports

Page 3: Airport Capacity Problem

• Mark Hansen, a UC Berkeley professor of Civil and Environmental Engineering and the Director of the National Center of Excellence for Aviation Operations Research: “a bullet train could provide congestion relief at major airports like LAX and SFO where costly delays are high and rising by cutting the number of passengers traveling to and from Los Angeles and San Francisco by air. These delays due to airport congestion could benefit high-speed rail.”

Page 4: Airport Capacity Problem
Page 5: Airport Capacity Problem

Methodology- Multi-commodity Flow model- Airports represented as nodes- Each node capacity based on the average of

the peak air traffic (in aircraft) for five days, over 1 year (data from the FAA’s Air Traffic Activity System Database)

- These are the limiting constraints

Page 6: Airport Capacity Problem

• Methodology (cont’d)• Supply and demand:• Set by a proportion determined by the

population of the cities and the distance between them. The distance factor forces a preference for regional flights over longer ones (distance from mapsoftheworld.com). Validated against FAA database.

• Based on a “Southwest” type airline

Page 7: Airport Capacity Problem

• Methodology (Cont’d)• Flow is restricted, and then the model is run to

see how many trains are needed to make up for reduced air carrying capacity.

• Train capacities assumed to be similar to 450 aircraft.

• Model will report “infeasible” until a acceptable number of trains is found.

Page 8: Airport Capacity Problem

• Methodology (Cont’d)• Model reports an infeasible solution until an

acceptable number of high speed rail support is added

• This is done by adding train nodes until the model finds a solution.

• All costs based on time.

Page 9: Airport Capacity Problem

• Next Three slides:• Division of country into regions• Sample airport to airport arcs (there are too

many to show on the chart, 169 to be exact)• Sample High Speed Rail set up. High Speed

Rail does not replace air routes. It merely augments them.

Page 10: Airport Capacity Problem

MidWest

SouthEast

NorthEastFocus AreaWest

Page 11: Airport Capacity Problem
Page 12: Airport Capacity Problem

Train Network Linking San Diego, Las Vegas and Los Angeles

Page 13: Airport Capacity Problem

Sample Route

LAXSTRT

LAXEND SEASTRT

SEAEND

Capacity = # flights, Cost = 0 (time)

Capacity = inf. flights, Cost = time of flight

Capacity = # flights, Cost = 0 (time)

Page 14: Airport Capacity Problem

Sample Route with Train(added capacity)

LAXSTRT

LAXEND TRNSTRT

TRNEND

Capacity = # flights, Cost = 0 (time)

Capacity = people. flights, Cost = time of train ride

Capacity = inf, Cost = 30 (time)

Dest. Train Sta.

Dest. Apt.

Capacity = inf, Cost = 30 (time)

Page 15: Airport Capacity Problem

Results

Page 16: Airport Capacity Problem

First Run

• Model can’t handle capacity (that’s good!). Only %55 of the total demand.

• Now, to add a train to a southern California arc (by adding train capacity) and see if that reduces the unmet demand.

• Goal is to reduce flights with the use of the trains. But, we are trying to show trains will make a difference in the first place.

Page 17: Airport Capacity Problem

Subsequent Runs

No Trains Trains0.25

0.35

0.45

0.55

0.65

0.75

% Demand Met (over the whole system)

Series1

Adding Three trains really didn’t help. Only a change of 1% in the demand not met.

Page 18: Airport Capacity Problem

A comparison

Without Trains (full)

Without Trains (10%)

Without Trains (20%)

Without Trains (30%)

With Trains(full) With Trains(10%) With Trains(20%) With Trains(30%)0.41

0.42

0.43

0.44

0.45

0.46

0.47

0.48

0.49

0.5

Capacities not Filled

Series1

Page 19: Airport Capacity Problem

% Interdiction vs. Demand not Met

0 10 20 300.41

0.42

0.43

0.44

0.45

0.46

0.47

0.48

0.49

0.5

Resiliency Curve (% interdiction)

Without TrainsWith Trains

Page 20: Airport Capacity Problem

Recommendations and Discussion• Flow based on a arbitrary ratio, using

population and distance (with a constant). Recommend a more accurate value for commodity flow.

• Also based on the entire population traveling, that might be a problem

Page 21: Airport Capacity Problem

If We Only Had More Time…• Account for the affect car commuters turned

train commuters would have on the capacities of the trains

• Network expansion nationwide• Cost in $$$ instead of time

Page 22: Airport Capacity Problem

One Last thing… what would happen if LA was leveled?

No LA, No Train No LA, with Train0.25

0.35

0.45

0.55

0.65

0.75

% Demand Met (LA Nuked)

Series1

Turns out, not much! (Almost the same as the previous slide)

Page 23: Airport Capacity Problem

• Bibliography• Federal Aviation Administration, Air Traffic Management System

and Database: http://aspm.faa.gov/opsnet/sys/Tracon.asp• Institute of Transportation Studies, U.C. Berkeley:

http://its.berkeley.edu/news/its/20110506• Los Angeles Airport News release:

http://www.lawa.org/newsContent.aspx?ID=1463• The National Center for Excellence for Aviation Operations

Research: http://www.nextor.org/• Maps of the World: http://

www.mapsofworld.com/usa/distance-chart/atlanta-ga.html• The Van Allen Institute, High Speed Rail Capacity and Use:

http://www.vanalen.org/lasr/theneedforspeed