Benefits of En Route Free Maneuvering and En Route Trajectory Negotiation during Off-Nominal Conditions
Dou Long*, Jing Hees†, and Shahab Hasan‡
LMI, McLean, Virginia
Abstract
The National Aeronautics and Space Administration (NASA) is conducting far-term research into a proposed concept for gate-to-gate national airspace system (NAS) operations called Distributed Air/Ground Traffic Management (DAG-TM) in which flight deck crews, air traffic service providers and aeronautical operational control facilities use distributed decision-making.
In this study we estimate the benefits of En Route Free Maneuvering and En Route Trajectory Negotiation in off-nominal conditions using empirical data. Specifically, the benefits we measure are the avoided disruption costs under inclement weather conditions due to the implementation of the two en route concept elements. The random nature of inclement weather makes the measurement of its impact on aviation a challenge. Since June 2003, the Department of Transportation’s Airline Service Quality Performance (ASQP) data reports the major airlines’ schedule/operation disruptions, in terms of flight cancellations, delays, and diversions, allocated to five cause categories, including extreme weather and non-extreme weather conditions. We extract the inclement weather-caused disruptions from the one-year period of July 2003 through June 2004 from the ASQP data. In developing the benefits pool, we recognize that these two concept elements’ functionalities and capabilities could not eliminate all disruptions caused by weather conditions. We estimate the percentage of weather caused disruptions that can be helped by the two concept elements based on expert opinion. We estimate the NAS-wide benefits for year 2004 by extending the ASQP results to the non-ASQP carriers via linear extrapolation. We also extrapolate current NAS benefits to the projected benefits in year 2015, the target year of DAG-TM deployment, by developing and applying forecast parameters to year 2004 benefits based on the traffic forecast. Finally, we translate the operational performance benefits of reduced delay and avoided diversions/cancellations into economic benefits using FAA and other published cost factors.
I. Introduction HE National Aeronautics and Space Administration (NASA) is conducting far-term research into a proposed concept for gate-to-gate national airspace system (NAS) operations called Distributed
Air/Ground Traffic Management (DAG-TM). DAG-TM is based on distributed decision making between flight deck crews, air traffic service providers (ATSP) and aeronautical operational control (AOC) personnel. The goal of DAG-TM is to increase system capacity/throughput, enable user preferences, and provide greater flexibility and efficiency, while meeting air traffic management (ATM) requirements and maintaining system safety and user accessibility to the NAS. DAG-TM will be accomplished with a human-centered operational paradigm enabled by procedural and technological innovations. These innovations include automation aids, information sharing and Communication, Navigation, and Surveillance (CNS) / ATM technologies. The total DAG-TM concept is intended to address all user classes (commercial carriers, general aviation, etc.) with an emphasis towards ensuring access to airspace resources
T
* Research Fellow, Technology Assessment and Resource Allocation, 2000 Corporate Ridge, McLean, VA 22102, AIAA Member. † Research Fellow, Technology Assessment and Resource Allocation, 2000 Corporate Ridge, McLean, VA 22102, AIAA Member. ‡ Program Manager, Technology Assessment and Resource Allocation, 2000 Corporate Ridge, McLean, VA 22102, AIAA Senior Member.
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for the entire user community. The full scope of DAG-TM is embodied in 15 Concept Elements (CEs) that define the concept across all flight phases (pre-flight planning, departure, cruise and arrival) and operational domains in the NAS (surface, terminal airspace and en route airspace).1
In prior studies, LMI conducted individual benefit/cost assessments of each of the following three
DAG-TM concept elements:2,3
En Route Free Maneuvering for User-preferred Separation Assurance and Local Traffic Flow
Management (TFM) Conformance. En Route Free Maneuvering, also designated as Concept Element 5 by NASA, enables autonomous aircraft to maneuver freely while maintaining separation assurance from potential hazards (traffic and area), and conforming to any local TFM constraints.4 This concept assumes air-to-ground data communications and an airborne decision support tool (DST) to support airborne self-separation, self- optimization and TFM constraint meeting. The ATSP manages unequipped aircraft with the aid of ground-based DST automation and generates conflict-free TFM restrictions to which free maneuvering aircraft must conform.
En Route Trajectory Negotiation for User-preferred Separation Assurance and Local TFM
Conformance. En Route Trajectory Negotiation, also designated as Concept Element 6 by NASA, is a trajectory-based air traffic control (ATC) concept.5 While the ATSP retains responsibility (and control) for separation assurance of all traffic, this concept integrates air and ground-based DST capabilities through data link to reduce ATSP workload and facilitate negotiation of user preferred trajectories (UPT) in the presence of traffic and TFM constraints. Although it contributes many benefits beyond the negotiation of UPTs, the term "trajectory negotiation" is retained in the title of this concept element for continuity with past publications.
Terminal Arrival Self-Spacing for Merging and In-Trail Separation. Terminal Arrival Self-
Spacing, also designated as Concept Element 11 by NASA, allows for equipped aircraft to merge into an arrival stream and maintain in-trail separation with a specified lead aircraft.6 This concept provides flight crews with traffic/intent data and spacing/merging guidance to enable allowing aircraft to operate in Instrument Meteorological Conditions (IMC) as if in Visual Meteorological Conditions (VMC). Airborne DSTs will be required to assist the flight crew in performing merging and spacing operations.
Our prior assessments for En Route Free Maneuvering and En Route Trajectory Negotiation were for
benefits under nominal conditions and measured the concept elements’ abilities in reducing delays and flight eliminations due to insufficient capacity of the NAS to accommodate forecasted demand. In other words, if the NAS capacity is not expanded sufficiently, there will be an economic loss to the nation as a portion of future demanded flights will not be scheduled and flown and those flights that remain will suffer increased delays. DAG-TM is anticipated to also deliver significant off-nominal benefits (e.g., mitigating throughput loss to inclement weather-impacted operations). The estimation of off-nominal benefits in this study is to measure the reductions of flight disruptions due to inclement weather conditions as the result of the implementation of En Route Free Maneuvering and En Route Trajectory Negotiation.
The methodologies which we applied to estimate the En Route Free Maneuvering and En Route Trajectory Negotiation benefit under nominal and off-nominal conditions were determined by the nature of benefit drivers, data availability, as well as the budget and time constraints.
For the benefit estimate in nominal conditions, a pre-DAG baseline was established in order to model traffic demand and the baseline capacity of future years 2015 and 2030 both with and without En Route Free Maneuvering and En Route Trajectory Negotiation implementation. In the nominal benefit estimating process, we assumed good weather conditions, so we could examine the benefits ‘purely’ from the comparison of demand and capacity.
For the benefit estimate in off-nominal conditions, we also established a pre-DAG baseline, which represents an annual level of weather-caused disruptions without En Route Free Maneuvering and En Route Trajectory Negotiation implementation. Due to schedule constraints, we could not conduct a detailed study based on LMI’s NAS models. Instead, we depended on empirical data to derive our benefit estimate to illuminate the benefit magnitude that En Route Free Maneuvering and En Route Trajectory Negotiation can provide in 2004 and 2015 under off-nominal conditions.
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II. Off-Nominal Conditions Benefit Study Objective and Methodology Overview Our objective in this short study was to estimate the range of benefits that could potentially be captured
by En Route Free Maneuvering and En Route Trajectory Negotiation in reducing flight disruptions due to off-nominal conditions; e.g., en route convective weather. The overall methodology for the benefit estimation is summarized by the following four steps:
1. Identify the flights that have been disrupted in off-nominal conditions using a historical database. 2. Estimate the capabilities of En Route Free Maneuvering and En Route Trajectory Negotiation, in
terms of the categories and percentages of disrupted flights that can be helped; i.e., estimate the candidate flights that would have not been disrupted given the existence of En Route Free Maneuvering and En Route Trajectory Negotiation.
3. Apply economic values to the candidate flights to calculate the economic benefits. 4. Extrapolate the benefits estimate, which is based on the extracted candidate flights in the database,
to the entire NAS, and to a future traffic demand level.
III. Data Sources for Disrupted Flights After evaluating various data sources, we decided to use the Department of Transportation’s (DOT)
Airline Service Quality Performance (ASQP) database as our primary data source. Any airline with more than one percent of total domestic enplanements is required to report its flight operations to ASQP, and other airlines can also volunteer to participate. In 2004, 18 airlines reported their flight operations to ASQP. We used one complete year of data, July 2003 through June 2004, in this study. Three general categories of disrupted flights are reported in ASQP:
• Delayed flights (15 minutes or more from scheduled arrival time) • Cancelled flights • Diverted flights
Since June 2003, ASQP has been collecting and reporting the reasons that flights were disrupted. Those reasons are summarized in Table 1.
Table 1. Codes of Disrupted Flights in ASQP
Carrier Weather
National Aviation System (NAS) Security
Late Arriving Aircraft
Cancellation Code A B C D N/A Delay Code E F G H I Diversion Code N/A N/A N/A N/A N/A
The categories and codes in ASQP are broad aggregations of flights disrupted for over a dozen more specific reasons. These reasons would be more helpful for us to identify the flights that can be helped by En Route Free Maneuvering and En Route Trajectory Negotiation, but the database contains only the codes in Table 1. The codes of the disrupted flights use the following general definitions:
• Air Carrier: The cause of the cancellation or delay was due to circumstances within the airline's control (e.g., maintenance or crew problems, aircraft cleaning, baggage loading, fueling).
• Weather (extreme): Significant meteorological conditions (actual or forecasted) that, in the judgment of the carrier, delays or prevents the operation of a flight. Examples of these conditions include tornado, blizzard, and hurricane.
• National Airspace System (NAS): Delays and cancellations attributable to the national airspace system that refer to a broad set of conditions—non-extreme weather conditions, airport operations, heavy traffic volume, air traffic control, etc.
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• Security: Delays or cancellations caused by evacuation of a terminal or concourse, re-boarding of aircraft because of security breach, inoperative screening equipment, and lines in excess of 29 minutes at screening areas.
• Late-arriving aircraft: A previous flight using the same aircraft arrived late, causing the present flight to depart late.§
IV. Candidate Flights Identification Based on the DAG-TM operational concept description documents, discussion with NASA
researchers, and interviews with subject matter experts such as airline pilots and dispatchers, we believe that En Route Free Maneuvering and En Route Trajectory Negotiation have the potential to help a subset of all flights disrupted by the weather.
Since the purpose of the disruption categories is to identify the party or organization in the best position to take corrective action in ASQP reporting, there is a fine line between some delays coded as “Weather (extreme)” and other coded as “NAS”, where “Weather” means there is no corrective action. Many disrupted flights under the “NAS” category are actually caused by inclement weather that could be remedied by corrective actions.
As a result, we believe the candidate flights that can be helped by En Route Free Maneuvering and En Route Trajectory Negotiation are those caused by inclement weather and reported under the “NAS” category. An estimated 20 to 40 percent of those flights can potentially be helped by En Route Free Maneuvering and En Route Trajectory Negotiation**. Thus we used these values as the lower and upper bounds of our benefit estimates. The percentage of delayed flights caused by inclement weather in the “NAS” category is given in Table 2. The weighted annual average from July 2003 to June 2004 is 69% for the total delayed flights and 79% for the total delayed minutes.
Table 2. Percentage of Non-Extreme Weather in NAS Delay Category††
Year And Month
Non-Extreme Weather Caused Delay As % Of
Total Delayed Flights In NAS Category
Non-Extreme Weather Caused Delay As % Of
Total Delayed Minutes In NAS Category
July 2003 82.14% 88.24% August 2003 82.55% 87.10% September 2003 59.82% 67.45% October 2003 53.47% 57.23% November 2003 65.19% 76.81% December 2003 63.41% 75.15% January 2004 66.32% 76.91% February 2004 66.34% 76.51% March 2004 63.70% 75.54% April 2004 61.35% 71.00% May 2004 78.19% 86.51% June 2004 76.98% 83.22% Data Source: DOT/BTS, Airline On-Time Statistics and Delay Causes, http://www.transtats.bts.gov/OT_Delay/OT_DelayCause1.asp.
§ In this study, this “induced” delay was further assigned to other categories according to the reason of delay of the previous flight, which was henceforth used in the benefit estimate. ** Captain O.L. (Butch) Sword, September 16, 2004, telephone interview with Shahab Hasan. †† The statistics are derived via a sampling of delayed flights conducted by the Bureau of Transportation Statistics (BTS).
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V. Economic Benefit Estimates This section describes our application of an economic benefit estimate to the set of disrupted flights
that can be helped by En Route Free Maneuvering and En Route Trajectory Negotiation. Figures 1 and 2 summarize the data processing flows.
Figure 1. Schematic of Benefit Estimate of Delayed Flights
OAG: Seats capacity
Output 2: Airlines delay valuation = operating cost per block hour * total delayed block hours
FAA passenger and airlines delay valuation All purpose
traveler’s time value per hour
Aircraft operating cost per block hour
Output 1: Passenger delay valuation = passenger time value per hour * total delayed hours
Airlines delay: Total delay block hours avoided
:
Passenger delay: Total passenger delay hours avoided
Benefit pool: Airlines delay
Delayed flights due to non-extreme weather
Total delayed block hours
DOT/BTS: Load factor by month
ASQP: Passenger delay ---
Flights delayed by cause based on flight schedule
Airline delay --- Flight delayed by cause based on planned block time
Benefit pool: Passenger delay
Delayed flights due to non-extreme weather
Total delayed minutes for passengers
% delayed flights in benefit pool that could be avoided due to free maneuvering and trajectory negotiation
Figure 2. Schematic of Benefit Estimate of Canceled Flights
ASQP: Canceled flights By cause
% canceled flights in NAS cause Category that free Maneuvering and Trajectory negotiation could have helped Potentially
Number of Canceled flights that could be avoided due to free maneuvering and trajectory
:
Benefit pool: Canceled flights due to non extreme weather
% canceled or diverted flights in benefit pool that could be avoided due to the implementation of free maneuvering and trajectory
Output: Cancellation reduction valuation = Direct cost avoided per flight * number of flights
Direct cost per canceled flight
In addition to ASQP, we used other databases in developing the economic benefit estimates. We used
the Official Airlines’ Guide (OAG), which lists most scheduled airline services in the world, to match the seat size of the disrupted flights. For the small percentage of flights that could not be matched to the OAG database, we used the BACK database to supplement the seat size information. For the calculation of enplanements and revenue passenger miles (RPM), we used the monthly load factors shown in the Bureau
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of Transportation Statistics (BTS) website. The yield data in the economic benefit estimate came from the Air Transport Association (ATA) monthly passenger yield report for domestic scheduled mainline services.
Benefit Estimates for Delayed Flights ise that some of the candidate flights would not be delayed
giv
delay code ‘I’, late-arriving aircraft, were considered as induced delay. For those flig
e schedule. Th
the airlines for the delayed flights is mainly dete
Table 3. Benefit Estimates to the Airlines from the Delayed Flights
Candidate Total Delay Cost/Delayed Total Cost Low End High End
The benefit estimate is based on the premen En Route Free Maneuvering and En Route Trajectory Negotiation, and the benefit was measured as
the delay cost that would have been eliminated. The cost of each delayed flight is assumed to beproportional to its delayed minutes, where the unit costs per delay minute are from the Federal Aviation Administration (FAA).‡‡
All delayed flights in hts, we used the aircraft tail number to identify the first delay of the day for each aircraft and then
applied the cause of that delay to all subsequent induced delay flights. From July 2003 to June 2004, 54% of induced delays were initially caused by “NAS”, so we reassigned these flights accordingly.
Flights are delayed by two kinds of delays: (1) against the block time§§, and (2) against the delays reported in ASQP are the delays against schedule, which measure the delays experienced by
passengers. But a flight departing late because of the late arrival of the previous leg may not have delay against its block time but will be late against its schedule. The delay against block time, which is not directly reported but imputed from the data from the recorded departure and arrival times in ASQP in the benefit estimate, measures just its portion of flight operation.
Ignoring the secondary effects, we assumed that the cost tormined by the sum of their delays against their block times, and that the cost to the passengers is
mainly determined by the delays against their schedules. Applying the percentages of the candidate flights that could potentially be helped by En Route Free Maneuvering and En Route Trajectory Negotiation, we obtained estimates of the benefits. Table 3 summarizes the lower and upper ends of our benefit estimates.
Flights Hours Hour Estimate Estimate
487,033 193,85 $3,262 $632.4 M $126.5 M $252.9 M 4
To derive the candidate flights for En Route Free Maneuvering and En Route Trajectory Negotiation off-
Table 4. Benefit Estimates to the Passengers from the Delayed Flights
Candidate Flights
Total Delay Hours
Cost/Delayed Hour
Total Cost Low End Estimate
High End Estimate
nominal benefit estimates, we first extracted all the delayed flights in the “NAS“ category, which was 56% of all the delayed flights (after adding NAS induced delays to this category). We then applied the DOT published percentage of non-extreme weather in the “NAS” delay category (see Table 2) to extract non-extreme weather caused delays. This step yielded a total of 487,033 candidate flights in the July 2003 through June 2004 period. The low- and high-end estimates result from the direct application of 20% and 40% percent, respectively, to the total cost. Similarly, we estimated the benefit of En Route Free Maneuvering and En Route Trajectory Negotiation to the passengers, using the passenger delay and cost, as summarized in Table 4.
487,033 31,734,240 $30.67 $973.3 M $194.7 M $389.3 M
‡‡ FAA-APO/ARCC (Draft Final Report, March 31, 2004): Economic Values for FAA Investment and Regulatory Decisions, A Guide. The hour value applied is air carrier all purpose travelers’ time value, which has been converted from 2000 dollar to 2004 dollar value using GDP deflator inflation index (published on NASA’s website: http://www.jsc.nasa.gov/bu2/inflateGDP.html).
§§ The block hours of a flight begin when the aircraft leaves the blocks before takeoff and end when it reaches the blocks after landing. Aircraft operating cost is expressed as dollars per block hour, and it is used in estimating air carriers’ delay cost.
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timBenefit Es ates for lled Flights e the e canc hts, we e gen ology t d
for t e delayed flights. We first extracted all the cancelled flights caused by the “NAS” category, which is 23% of all the cancelled flights. Since there is no direct information regarding the percentage of inclement
AS” category, we then applied the same percentage, the 69%
C te High End Estimate
CanceTo estimat benefits of th elled flig used the sam eral method hat we useh
weather-caused cancellations within the “Nweighted average, as for the delayed flights (see Table 2) to extract non-extreme weather caused cancellations in the “NAS” category. This step yielded 17,171 candidate flights during the period of July 2003 through June 2004, or 16% of the total cancelled flights (16% = 23% * 69%).
Since the FAA has not published any cost figures for cancelled flights, we used $11,500 per cancelled flight.7 Again assuming that En Route Free Maneuvering and En Route Trajectory Negotiation apply to 20% to 40% of the candidate flights, we obtained benefit estimates in Table 5.
Table 5. Benefit Estimates of Cancelled Flights
andidate Flights Cost/Cancellation Total Cost Low End Estima
17,171 $79.0 M $11,500 $197.5 M $39.5 M
ble t tio seng flig
included a separate cost estimate for passengers. The Shavell figure is about twice the revenue of the avera stic flight, but o inform at is inclu neral, the cost lled
ight includes the lost revenue, crew cost reallocation, aircraft repositioning, airline paid passenger meals, ote
ost per diverted flight. This figure is subject to much of the same the cost estimates.
ights poses another challenge. Since ASQP does not have any
C Cost/Cancellation Total Cost Low End Estimate High End Estimate
We were una o find any informa n on the pas er cost of cancelled hts, so we have not
ge dome we have n ation on wh ded. In ge of a canceflh ls, airline staff overtime cost (paid to both crew and ground personnel), and other structural costs like ground equipment arrangement. However, some of the lost revenue may be recovered by passengers taking later flights on the same airline. The passenger costs may have also been included in Shavell’s figure, but we could not verify that assumption.
Benefit Estimates for Diverted Flights A flight diversion is the most expensive of the potential disruptions facing airlines. We used Shavell’s
estimate of $22,000 as the average c 7
uncertainty about what is included inEstimating the number of candidate fl
data fields for capturing why flights were diverted, we assumed that 16% of the diverted flights are candidate flights (the same percentage for the canceled flights). Based on this assumption, the total number of candidate flights was 2,028 for the period of July 2003 through June 2004. The benefit estimates are given in Table 6.
Table 6. Benefit Estimates for Diverted Flights
andidate Flights
2,028 $17.8 M $22,000 $44.7 M $8.9 M
Benefit Estimates SuTa sts the benefit estimates for the thr f disrupted s we have not sly,
these s are subject t sumption s of the un s involved, ou s of the benefits of delayed flights are fairly solid, while those for the cancelled flights have more assumptions,
even more assumptions. Fortunately, our results are dominated by the delay
mmary ble 7 liestimate
ee kinds os. In term
flights. Acertaintie
ed previour estimateo many as
with the diverted flights havingreduction benefits.
Despite the uncertainties and the assumptions, we are confident that the benefit estimates provide a reasonable range of benefits attributable to En Route Free Maneuvering and En Route Trajectory
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Negotiation under off-nominal conditions -- approximately $500 million for the 2004 level of traffic demand.
Table 7. Benefit Estimates, Based on July 2003 - June 2004 ASQP Data
Low Estimate ($M) High Estimate ($M)
Delay Reduction to Airlines 126.5 252.9 Delay Reduction to Passengers 194.7 389.3
NAS-Wide Bene and 2015 We extrapolated disruptions’ benefit estimates to obtain total NAS En Route Free
Maneuvering and En Route Trajectory Negotiation benefits using different parameters. Each type of fferent valuation methods and extrapolating parameters. data to separate all carriers into two groups: ASQP
car
extrapolation parameters, we assumed that non-ASQP and ASQP fights f the total flights that can be helped by En Route Free Negotiation
We mad formation to provide a basis for changing
them. T ws: SQP total flights/ASQP carriers’ total flights)*(non-
ASQP operating cost per block hour/ASQP carriers’ operating cost per block hour)
Sincflight, their
carriers’ average stage length) * (non-ASQP operating cost per block hour/ASQP carriers’
Extrap tiExtrapol
and the non if NAS apt to the constrained NAS by changing
ome areas. A primary driver for the actual var
fit Estimates for 2004 three types of
disruptions has its own cost drivers, so it requires diIn applying these cost drivers, we used FAA
riers and non-ASQP carriers. We then used such cost drivers as enplanements, revenue passenger miles (RPMs), number of operations/departures, stage length, and block hour operation costs to develop estimates of various cost components.
Extrapolating from ASQP-only to Entire NAS The NAS flights are all the flights operated by the commercial carriers in the domestic airports,
excluding cargo. For the delay• are subject to the same percentage o
Maneuvering and En Route Trajectory• have the same average delay per delayed flight, and • share the same passenger cost per minute
e these assumptions because we had no additional inhe resulting extrapolation parameters (inflators) are as follo• Airline cost non-ASQP inflator = (non-A
e our original cost estimates for cancelled and diverted flights were based on the costs per disrupted non-ASQP inflator is as follows:
• Cancellation/diversion cost non-ASQP inflator = (non-ASQP average stage length/ASQP
operating cost per block hour) * (non-ASQP total flights/ASQP carriers’ total flights)
ola ng Current NAS Benefits to the Benefits in 2015 ating the benefits in the current NAS to a future NAS is highly speculative. With traffic growth -linear nature of NAS operations, the percentages of disrupted flights will increase
capacities are kept constant. On the other hand, the airlines may adtheir operations. NAS capacities are also likely to increase in s
iation in future off-nominal benefits will be the weather and its location and timing with respect to NAS traffic flows. Since the future effects of weather are essentially random and cannot be accurately forecasted, we further assumed that our analysis represented the typical effects of weather (in terms of average frequency and extent) for future years.
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In addition, our extrapolation methodology assumed that all percentages will be unchanged from their 2004 levels. The only changes from the current NAS to the future NAS is traffic demand level. Airline delay, cancellation, and diversion costs are directly related to the flight operation growth, while passenger dela
y cost is directly related to the passenger enplanements growth. Both of these growth rates were derived from the FAA’s Terminal Area Forecast (TAF).
Table 8 shows the extrapolation (ASQP benefits to NAS-wide benefits) and forecasting parameters (2004 NAS benefits to 2015 NAS benefits) parameters.
Table 8. Extrapolation and Forecast Parameters for 2004 NAS and 2015 NAS
Extrapolating Parameter Forecast Parameter
Cost of Airline Delay 1.085 1.24 Cost of Passenger Delay 1.218 1.43 Cost of Cancellation and Diversion
1.034 1.24
VI. Results and Conclusions Tables 9 and 10 show the benefit estimates for the current NAS traffic demand and that forecasted for
2015. We derived these estimates by le 8 by the ASQP-only estimates in Table 7.
M)
multiplying the parameters in Tab
Table 9. NAS-Wide Benefit Estimate, 2004 Demand (in 2004 dollars)
Low Estimate ($M) High Estimate ($
Delay Reduction to Airlines 137.3 274.5 Delay Reduction to Passengers 237.1 474.3 Cancellation Reduction 40.8 81.7 Diversion Reduction 9.2 18.4 Total 424.4 848.8
Table 10. NAS-Wide Benefit Estimate Demand (in 2004 d )
)
, 2015 ollars
Low Estimate ($M) High Estimate ($M
Delay Reduction to Airlines 170.3 340.5
Delay Reduction to Passengers 294.0 588.0 Cancellation Reduction 50.0 110.0
Diversion Reduction 11.0 22.0
Total 525.7 1,050.5
Our discussion about the uncertainties and necessary assumptions that accompanied the
nta ASQP-only results also applies here to S-wide benefit esti onetheless, we e still confident that these results provide a good estimate of the possible range of benefits attributable to
En
d
previous tion ofprese
ar the NA mates. N
Route Free Maneuvering and En Route Trajectory Negotiation under off-nominal conditions: approximately $500 M for 2004 traffic demand and growing to about $750 M for 2015 traffic demand.
Our off-nominal estimates of benefits primarily considered the functionality and benefit mechanisms of En Route Free Maneuvering; we believe that En Route Trajectory Negotiation would achieve only a fraction of those benefits. In other words, all of the benefits we estimated for off-nominal conditions coul
9
go t
dollars)
Maneuvering Benefit)
o En Route Free Maneuvering because those flights are ”autonomous”, while only a small portion of the off-nominal benefits would be achieved by En Route Trajectory Negotiation since those flights are still managed by ground air traffic controllers. We estimated En Route Free Maneuvering and En Route Trajectory Negotiation nominal condition benefits in prior work,5 and the ratio of 2015 En Route Trajectory Negotiation and 2015 En Route Free Maneuvering benefit estimates is 0.82 ($654M/$799M); i.e., En Route Trajectory Negotiation implementation achieves 82% of the En Route Free Maneuvering benefits under nominal conditions (assuming 100% equipage of the fleet). Based upon our understanding of En Route Free Maneuvering and En Route Trajectory Negotiation functionalities, we believe that the benefits ratio between these two concept elements in off-nominal conditions would be smaller than the benefits ratio in nominal conditions. Our rough assessment is that En Route Trajectory Negotiation may be able to achieve about 20 to 25 percent of En Route Free Maneuvering’s benefits. Table 11 reflects this rough assessment but additional work is necessary for verification or refinement.
Table 11. En Route Free Maneuvering and En Route Trajectory Negotiation NAS-Wide Off-Nominal
Condition Benefit Estimate, 2004 and 2015 Demand ($M in 2004
En Route Free Maneuvering En Route Trajectory Negotiation (25% of En Route Free
Low Estimate High Estimate Low Estimate High Estimate
Our show that n Route Fr euvering an oute Traject gotiation will
provide t benefit f-nominal s; e.g., if te Free Ma ing had been plemented in 2004, about a half billion dollars could have been saved during inclement weather
con
The authors would like to acknowledge NASA’s Advanced Air Transportation Technologies (AATT) Project as the sponsor of this work. In o thank Steve Green of NASA Ames Research Center, for providing technica l as encouragement and friendship.
1. , S., Bilimoria, K., and Ballin, M. G., “Distributed Air-Ground Traffic Management for En Route flight Operations”, Air Traffic Control Quarterly, Distributed Air/Ground Traffic Management, Volume 9, Number 4, De
3. Cycle Cost/Benefit Assessments of Distributed
4. e
ld, CA.
results both E ee Man d En R ory Nesignifican s in of condition En Rou neuver
imditions by U.S. airlines through delay reduction, avoided detours, and avoided cancellations. In year
2015, the estimated benefits in off-nominal conditions are comparable in magnitude with the estimated benefits in nominal conditions. It is evident that the two en route concept elements provide effective potential solutions for the en route congestion problem in both nominal and off-nominal conditions.
VII. Acknowledgements
particular, we would like tl direction and review, as wel
VIII. References Green
Special Issue oncember, 2001
2. Hasan, S., Leiden, K., Mondoloni, S., Kozarsky, D., and Green, S., “An Initial Benefits Assessment of Distributed Air/Ground Traffic Management Concepts”, AIAA 2003-6806, November 2003. Stouffer, V., Hasan, S., and Kozarsky, D., “Initial Life-Air/Ground Traffic Management Concept Elements”, AIAA 2004-6452, September 2004. National Aeronautics and Space Administration (2002), DAG-TM Concept Element 5 En Route FreManeuvering Operational Concept Description, Advanced Air Transportation Technologies (AATT)Project, NASA Ames, Moffett Field, CA.
5. National Aeronautics and Space Administration (2003), DAG-TM Concept Element 6 En Route Trajectory Negotiation Operational Concept Description, Advanced Air Transportation Technologies (AATT) Project, NASA Ames, Moffett Fie
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6. National Aeronautics and Space Administration (2002), DAG-TM Concept Element 11 TerminalArrival Self-Spacing Operational Concept Description, Advanced Air Transportation Technologies (AATT) Project, NASA Ames, Moffett Field, CA.
s,”
8. 004): Economic Values for FAA Investment and
9. stration (2003), Single-Year, NAS-Wide Benefits Assessment of
offett Field, CA.
11. 12. ry Decisions, A Guide.
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