Airport Congestion: Demand Management Strategies and Equity Issues - PowerPoint PPT Presentation

Giovanni ANDREATTA (Padova University) Guglielmo LULLI (Milan “Bicocca” University) Airport Congestion: Demand Management Strategies and Equity Issues Bressanone, July 2007 G.Andreatta (PADOVA University) 1

Background • My Runggaldier number is = • We have known each other for the past … • We were together in Rome when my wallet • Hiking and Skiing (Val Mesdì,Lagorai, Fanes) • Moving to Padova • Gordon Kaufman and MIT Bressanone, July 2007 G.Andreatta (PADOVA University) 2

Main findings: A theorem about existence and unicity Dear Wolfgang, … grazie di esistere ! (thanks for existing) Bressanone, July 2007 G.Andreatta (PADOVA University) 3

Air Traffic Demand vs AT Capacity • Fast and steady increase of demand (with exceptions: 11 September 2001, SARS, etc. ...) • Modest increase of capacity Need to address demand Bressanone, July 2007 G.Andreatta (PADOVA University) 4

Bressanone, July 2007 G.Andreatta (PADOVA University) 5

How to cope with demand Peaks • Administrative measures (SLOT Assignment, etc.) • Market Based Demand Management strategies (Congestion fee, Auctions, etc.) Bressanone, July 2007 G.Andreatta (PADOVA University) 6

This presentation will touch upon … • Analysis of a combination of a queuing model and a model of the elasticity of airport demand to airport charges. • Equity issues • Congestion pricing vs Auction mechanism Bressanone, July 2007 G.Andreatta (PADOVA University) 7

Demand Management Strategies should • Limit demand for access to busy airfields and/or congested airspace during peak periods of time • Modify temporal and/or spatial distribution of demand (not presented today) Bressanone, July 2007 G.Andreatta (PADOVA University) 8

Objective of Demand Management Policies … Enhance the efficiency of aircraft operations in European airspace and airports, while interfering to the least possible extent with the overarching aim of creating a competitive, market-driven air transport environment in Europe … Bressanone, July 2007 G.Andreatta (PADOVA University) 9

What has already been addressed • Peak period pricing in general (widely investigated) • Applications to congestion-pricing of transportation facilities (more recent) • Applications to air transportation (fewer) – Concentrated on airport congestion – Very limited work (unpublished) on airspace side Bressanone, July 2007 G.Andreatta (PADOVA University) 10

Market based Demand Management (MbDM) strategies • Congestion fee approach: the AA decides access fees, the “market” will respond with an actual demand “lower” than the original one • Auction approach: the AA decides the level of acceptable demand (how many movements), the “market” will assess the appropriate access price Bressanone, July 2007 G.Andreatta (PADOVA University) 11

Congestion fee vs. Auction approaches Assuming that the demand function is known: • A congestion fee decreases the original demand: the AA decides the fee and can “compute” the actual demand • With an Auction: the AA decides the “actual demand” and can compute a “threeshold” τ : the bids above τ are accepted Bressanone, July 2007 G.Andreatta (PADOVA University) 12

Equity issues In the presence of different categories should the imposed prices be the same for all categories? Bressanone, July 2007 G.Andreatta (PADOVA University) 13

The cost of Congestion Congestion costs due to any specific user have 2 components: – Cost of delay to that user (internal) – Cost of delay to all other users caused by that user (external) This second component can be very large! Bressanone, July 2007 G.Andreatta (PADOVA University) 14

Optimal congestion fee A congestion fee on a user is optimal when it is equal to the external costs that the user imposes on the other users. In practice it is usually very hard to: – Estimate external marginal delay costs Queuing Theory has much to offer Bressanone, July 2007 G.Andreatta (PADOVA University) 15

Objective of the Airport example • To provide through the analysis of an example a demonstration of the overall approach • To offer through the example a proof of concept , i.e., an indication of the types of benefits (and costs) that can be obtained Bressanone, July 2007 G.Andreatta (PADOVA University) 16

Airport illustrative example Parameter Type 1 Type 2 Type 3 (HEAVY) (MEDIUM) (LIGHT) 80 90 100 Service rate (movements per hour) 10 10 10 Standard deviation of service time (seconds) seconds seconds seconds Cost of delay time ($ per hour) $5,000 $3,000 $800 Bressanone, July 2007 G.Andreatta (PADOVA University) 17

Demand functions (hypothetical) λ = − ⋅ − ⋅ 2 ( ) 40 0 . 5 2 . 5 x x x 1 λ = − ⋅ − ⋅ 2 ( ) 50 1 . 5 5 . 0 x x x 2 λ = − ⋅ − ⋅ 2 ( ) 60 5 . 0 20 . 0 x x x 3 where : x = DC + CF DC = cost of the delay time experienced by the aircraft CF = congestion fee paid by the aircraft to land or to take off from Airport Bressanone, July 2007 G.Andreatta (PADOVA University) 18

40 50 60 0,001 0,003 0,01 Demand Functions for three types of users 0,00001 0,00002 0,00008 x lambda 1 lambda 2 lambda 3 0 40 50 60 Arriv al rate (Users/unit tim e) 70 100 39,8 49,5 58,2 200 39,4 48,6 54,8 60 300 38,8 47,3 49,8 400 38 45,6 43,2 500 37 43,5 35 50 600 35,8 41 25,2 Type 1 700 34,4 38,1 13,8 40 800 32,8 34,8 0,8 Type 2 900 31 31,1 -13,8 30 Type 3 1000 29 27 -30 1100 26,8 22,5 -47,8 20 1200 24,4 17,6 -67,2 1300 21,8 12,3 -88,2 10 1400 19 6,6 -110,8 1500 16 0,5 -135 0 1600 12,8 -6 -160,8 1700 9,4 -12,9 -188,2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1800 5,8 -20,2 -217,2 2 4 6 8 0 2 4 6 8 0 1 1 1 1 1 2 1900 2 -27,9 -247,8 2000 -36 -280 Total cost ($)

Case 1: No congestion fee Type 1 Parameter Type 2 Type 3 Delay cost (DC) per aircraft $3,224 $1,935 $515 Congestion fee (CF) $0 $0 $0 Total cost of access $3,224 $1,935 $515 (DC + CF) Demand (no. of movements per 12.4 28.4 52.1 hour) Total demand (no. of 92.9 movements per hour) Expected delay per aircraft 38 minutes 42 seconds Utilization of the airport 99.01% (% of time busy) Bressanone, July 2007 G.Andreatta (PADOVA University) 20

Congestion Pricing and Queuing Theory Consider a queuing facility with a single type of customer in steady-state. Let: c = delay cost per unit of time/customer C = total cost of delay per unit time W q = Expected queuing time per customer λ = demand rate = = λ C cL c W Then: q q Bressanone, July 2007 G.Andreatta (PADOVA University) 21

Marginal Cost = = λ C cL c W From q q dW dC it follows = = q + λ q MC c W c λ λ d d where: c = (delay) cost per unit time per customer W q = Expected queuing time per customer λ = demand rate Bressanone, July 2007 G.Andreatta (PADOVA University) 22

Optimal congestion fee A congestion fee on a user is optimal when it is equal to the external costs that the user imposes on the other users. For an M/G/1 queue: dW dC = = q + λ q MC c W c λ λ d d Marginal Internal External = + cost cost cost Bressanone, July 2007 G.Andreatta (PADOVA University) 23

Optimal congestion fee • The external cost can be explicitly computed (under suitable assumptions) even in the presence of several categories of users • In the presence of several categories the external costs might be different (so are the congestion fees!) Bressanone, July 2007 G.Andreatta (PADOVA University) 24

Case 2: Optimal* congestion fee Optimal Congestion Fee Delay cost (DC) per aircraft $250 $150 $40 Congestion fee (CF) $1,712 $1,504 $1,341 Total cost of access $1,962 $1,654 $1,381 (DC + CF) Demand (no. of movements per 29.4 33.8 14.9 hour) Total demand (no. of 78.1 movements per hour) Expected delay per aircraft 3 minutes 0 seconds Utilization of the airport (% of 89.2% time busy)

Congestion fee approach vs. “do nothing” approach By charging a congestion fee equal to the external delay costs, we have: • Greatly reduced the average delay per aircraft (3’0’’ vs. 38’42’’) • Greatly reduced the delay costs per aircraft ($250 from $3,224, $150 from $1,935, $40 from $515) • Reduced the total cost of access for most aircraft ($1,962 from $3,224, $1,654 from $1,935, $1,381 from $515) • Assuming Type I, (resp. II, III) carry 200 (resp. 100, 20) pax on average per a/c: the total no. of pax will be increased by 50% (9,558 from 6,362) Bressanone, July 2007 G.Andreatta (PADOVA University) 26

Demand Functions for three types of users Arrival rate (Users/unit time) 70 60 o 50 Type 1 o 40 + Type 2 30 + Type 3 20 + o No Fee 10 o + With Fee 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 4 6 8 0 2 4 6 8 0 1 1 1 1 1 2 Total cost ($) Bressanone, July 2007 G.Andreatta (PADOVA University) 27

Equity Issues • By using a pure MbDM approach, some categories might experience an untolerable burden (e.g., Type 3 aircraft). In the worse situation a category could have almost no access to the airport • There is a need to mitigate this risk • Who should evaluate equity ? Bressanone, July 2007 G.Andreatta (PADOVA University) 28