Benefits Assessment Methodology for an Air Traffic Control Tower - - PowerPoint PPT Presentation

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Benefits Assessment Methodology for an Air Traffic Control Tower - - PowerPoint PPT Presentation

Benefits Assessment Methodology for an Air Traffic Control Tower Advanced Automation System Tom Reynolds, Rich Jordan, Masha Ishutkina, Rob Seater & Jim Kuchar 10 th AIAA Aviation Technology, Integration and Operations (ATIO) Conference Fort


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SLIDE 1

MIT Lincoln Laboratory

Slide-1 TGR 9/14/2010

Benefits Assessment Methodology for an Air Traffic Control Tower Advanced Automation System

10th AIAA Aviation Technology, Integration and Operations (ATIO) Conference Fort Worth, TX -- 13-15 September 2010

Tom Reynolds, Rich Jordan, Masha Ishutkina, Rob Seater & Jim Kuchar

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SLIDE 2

MIT Lincoln Laboratory

Slide-2 TGR 9/14/2010

Outline

  • Overview of system
  • Need for benefits assessment
  • Methodology
  • Application/Data analysis
  • Results: Informing system development priorities
  • Summary
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SLIDE 3

MIT Lincoln Laboratory

Slide-3 TGR 9/14/2010

Tower Flight Data Manager (TFDM)

  • Integrated tower system being considered for development by FAA

Operational Users

Tower controllers Flight data, Clearance, Ground, Local, Supervisor TRACONs, ARTCCs Flight Operations Centers Ramp Tower Airport Authority

Weather / Hazards Terminal and Surface Surveillance

Surveillance Display Flight Data Manager

Flight Plan Data Traffic Flow Constraints

Decision Support Tools (DSTs)

Flight Operations Data

Remote / Enhanced Visual Awareness

Benefits

Robust operations Reduced delay, fuel, environmental impact Enhanced safety Ability to support remote

  • perations: Staffed NextGen

Tower (SNT)

Tower Flight Data Manager

Net-centric Infrastructure

External Sources Enablers

Consolidated tower systems Enhanced cross-domain information exchange Decision support tools

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SLIDE 4

MIT Lincoln Laboratory

Slide-4 TGR 9/14/2010

Need for Benefits Assessment

  • Quantifies how well the

new system performs relative to baseline

  • Needed for Investment

Analysis to make business case for continued development and/or deployment

  • Leads to understanding
  • f system inefficiencies

and causality to help guide capability development

Time Performance Metric

Baseline system New system

Increasing demand

New system benefits

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SLIDE 5

MIT Lincoln Laboratory

Slide-5 TGR 9/14/2010

FAA Standard Benefits Assessment Methodology

  • FAA defines 11-step benefits analysis methodology
  • Distilled version:
  • 1. Understand the program
  • 2. Identify relevant performance metrics
  • 3. Identify current & future “baseline” system

performance

  • 4. Identify current & future “new” system performance
  • 5. Define the benefits impact
  • 6. Convert to economic values and compare to costs
  • 7. Report
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SLIDE 6

MIT Lincoln Laboratory

Slide-6 TGR 9/14/2010

TFDM Benefits Assessment Methodology

  • 1. Understand the new

system

  • 2. Identify relevant

metrics

  • 3. Establish baseline

metric values

  • 4. Establish new

system metric values

  • 5. Define the benefits

impact

  • 6. Convert to economic

values and compare to costs

  • 7. Report

Metric Time

TFDM Baseline

  • 6a. TFDM Costs

Inefficiency & causality identification

Archived Data

e.g. ASPM, ASDE-X Monetization

Future System Forecasts

e.g. TAF, FACT

  • 2. Metric

Identification

  • 3b. Future Baseline

System Metric Predictions

  • 3a. Current Baseline

System Metric Predictions

  • 1. ConOps

Functional Reqts Operatl Assessment

  • 4a. TFDM Capability

Development

  • 4b. Future TFDM

System Metric Predictions (Alternative 1..n)

  • 6b. TFDM Cost / Benefit

Analysis

  • 7. Report
  • 5b. TFDM Benefits

+ - +-

  • 5a. Benefits Claimed

by Other Systems +-

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SLIDE 7

MIT Lincoln Laboratory

Slide-7 TGR 9/14/2010

TFDM Benefits Assessment Methodology Application

  • Step 1: Primary objective of TFDM is to improve efficiency of

surface operations

  • Step 2: Taxi-out delay time & fuel burn performance metrics
  • Step 3a: Current baseline system performance

– ASPM analysis – ASDE-X analysis

  • Step 3b: Future baseline system performance

– Queuing model

  • Step 4a: Informing TFDM capability development
  • Step 4b: Future TFDM system performance
  • Step 5/6/7: TFDM cost/benefit analysis and report
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SLIDE 8

MIT Lincoln Laboratory

Slide-8 TGR 9/14/2010

TFDM Investment Analysis Airports

BOS ADW JFK EWR LGA PVD SEA SFO LAX ANC PDX HNL LAS DEN DFW IAH HOU SLC SNA SAN PHX STL ORD MDW MSP MSY MKE SDF MEM MCI MCO MIA FLL ATL CLT DTW CVG DCA IAD BWI PHL PIT CLE BDL

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SLIDE 9

MIT Lincoln Laboratory

Slide-9 TGR 9/14/2010

Current Baseline System Performance ASPM Analysis

  • FAA Aviation System Performance Metrics (ASPM) data

extracted for analysis airports

  • Taxi-out delay time: average versus unimpeded push-back-

to-wheels-off time

  • Taxi-out delay fuel: Delay time x Fleet-mix-weighted fuel flow

– Fuel flow for individual aircraft from ICAO ground idle rate – Assumes all delay absorbed with engines on (upper bound)

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SLIDE 10

MIT Lincoln Laboratory

Slide-10 TGR 9/14/2010

Current Baseline System Performance ASPM Analysis (2008)

0% 20% 40% 60% 80% 100% 120% 140% 20 40 60 80 100 120 140 160 180 200 220 240 260 280

ANC ATL BDL BOS BWI CLE CLT CVG DCA DEN DFW DTW EWR FLL HNL HOU IAD IAH JFK LAS LAX LGA MCI MCO MDW MEM MIA MKE MSP MSY ORD PDX PHL PHX PIT PVD SAN SDF SEA SFO SLC SNA STL Time Fuel % Increase over unimpeded

Total Taxi-out Delay Time (hours/day) Total Taxi-out Delay Fuel (tonnes/day) Taxi-out Delay % Increase Over Unimpeded (100% = Actual Taxi-out Time or Fuel is Double Unimpeded)

Average total delay: 2533 hrs/day (925 khrs/yr), 1874 tonnes/day (684 ktonnes/yr)

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SLIDE 11

MIT Lincoln Laboratory

Slide-11 TGR 9/14/2010

Current Baseline System Performance ASDE-X Analysis

  • Airport Surface Detection

Equipment-Version X (ASDE-X) surveillance allows identification

  • f location of delay on surface

– Gate – Spot – Queue – Runway

ASDE-X

  • At these locations, inefficiencies can be observed & control

mechanisms applied

  • ASDE-X data from Dallas-Fort Worth (DFW) airport analysed

– TFDM prototype site

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SLIDE 12

MIT Lincoln Laboratory

Slide-12 TGR 9/14/2010

Current Baseline System Performance ASDE-X Analysis

Gate Spot Runway Queue

Performance Metric: e.g. Total Taxi-out Time

Runway Enter Wheels-off

Benefit gained from TFDM Alternative n Remaining “avoidable” delay “Unavoidable” delay Taxi-out Delay “Benefits pool”

Spot delay Runway queue delay Position & hold

Ramp Taxi Runway Queue

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SLIDE 13

MIT Lincoln Laboratory

Slide-13 TGR 9/14/2010

Current Baseline System Performance ASDE-X Analysis

  • ASDE-X observed delay:

6.1 mins

  • ASDE-X delay wrt 10th %ile:

4.1 mins

  • ASPM delay wrt 10th %ile:

4.3 mins

VMC n≈3000 IMC n≈1500

Taxi-out Delay Relative to Unimpeded (mins)

11 10 9 8 7 6 5 4 3 2 1

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SLIDE 14

MIT Lincoln Laboratory

Slide-14 TGR 9/14/2010

Future Baseline System Performance Queuing Model

  • Investment analysis period: 2015-2035
  • Queuing model developed to project taxi-out delay time & fuel at

analysis airports into future

  • Assumptions:

– Runway is dominant airport constraint – Poisson demand rates – Exponentially-distributed service times

  • Model inputs:

– Demand: FAA Terminal Area Forecast – Capacity: FAA FACT2 Airport Capacities (2007-2025, no increase 2025-2030) – Average delay capped at 15 mins in VMC and 45 mins in IMC (consistent with system evolving when delays increase)

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SLIDE 15

MIT Lincoln Laboratory

Slide-15 TGR 9/14/2010

Future Baseline System Performance Queuing Model

1 2 3 4 5 6 7 2005 2010 2015 2020 2025 2030 2035 2040

Year

Annual Runway Queueing Delay Time Across 43 Airports (Relative to 2008)

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SLIDE 16

MIT Lincoln Laboratory

Slide-16 TGR 9/14/2010

Future Baseline System Performance Queuing Model

10 20 30 40 50 60 70 80 90 100 20 40 60 80 100

% Cumulative Runway Queuing Delay Reduction

Unavoidable Delay (notional) Claimed by

  • ther

systems (notional)

Cumulative Runway Queueing Delay Time Across 43 Airports (Relative to 2008)

Unique savings available to TFDM (notional)

  • TFDM capabilities

should be designed to deliver benefits against this portion

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SLIDE 17

MIT Lincoln Laboratory

Slide-17 TGR 9/14/2010

Informing TFDM Capability Development

  • Mapping delay location to possible causality

Location

  • f Delay

Identified Causes TFDM Opportunities Ramp Aircraft not ready Situational awareness Ground crew not ready Situational awareness Ramp blocked Situational awareness Forgotten at spot Efficiency improvement Back propagation of delay Indirect impact Taxi Runway crossings required Situational awareness Long taxi route Efficiency improvement Taxiway capacity limit Efficiency improvement Queue Runway crossings by others Situational awareness No airborne route available Efficiency improvement Runway capacity limit Efficiency improvement Inefficient departure sequence Efficiency improvement Runway Aircraft not ready Situational awareness Runway crossings by others Situational awareness Aircraft performance Situational awareness No airborne route available Efficiency improvement

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SLIDE 18

MIT Lincoln Laboratory

Slide-18 TGR 9/14/2010

Informing TFDM Capability Development

  • Mapping causality to TFDM capability development opportunities

Identified Causes Benefits Mechanism Candidate TFDM Capability Key Enabling Capabilities Observations & Analysis Forgotten at spot Prevent waiting aircraft from being

  • verlooked

Notify controllers when aircraft is at spot for long time Predict normal spot wait time Frequency of

  • ccurrence;

Assess proper threshold Long taxi route Avoid long taxi routes if shorter alternatives exist Assign efficient taxi routes, accounting for upcoming runway configuration changes Predict upcoming RW configuration changes; Taxi time modeling Presence of alternative routes; Taxi time model accuracy Taxiway/ runway capacity limit Manage demand on taxiway/runway to match capacity Recommend spot release times to meter surface traffic Surface queuing models to predict congestion Frequency of

  • ccurrence and

correlated conditions; Ideal queue length No airborne route available Get aircraft to runway (only) when route is available Predict route blockage and manage spot release time to achieve needed runway time Departure route availability analysis; Taxi time modeling Frequency of

  • ccurrence;

Reliability of route availability forecasts Inefficient departure sequence Increase dep.

  • seq. efficiency

Manage spot release times to improve sequence Predict dep. sequence; Sequence

  • ptimization

Comparison to

  • ptimal

sequence

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SLIDE 19

MIT Lincoln Laboratory

Slide-19 TGR 9/14/2010

Summary

  • New integrated air traffic control automation system being

developed

  • Importance of benefits assessment in system development

– Business case – Inform development priorities

  • Methodology for benefits assessment presented, with

sample applications and data analysis

  • Illustrated insights for TFDM development