In Service Demonstration of Advanced Arrival Techniques at Schiphol Airport

Joseph Wat1, Jesse Follet2, Rob Mead3, and John Brown4

The Boeing Company

and

Robert Kok5, Ferdinand Dijkstra6, and Jeroen Vermeij7

Luchtverkeersleiding Nederland (LVNL)

From 8 January 2006 until 15 March 2006 a trial was conducted where aircraft utilized a Continuous Descent Arrival (CDA) technique starting from the cruising flight level to the final approach at Amsterdam Airport Schiphol. Boeing, Maastricht UAC, ATC the Netherlands, Martinair and Transavia airlines were conducting this trial in order to assess if the advanced aircraft capabilities can be used during the arrival phase of flight to improve the ATM System. The assessment of ATM System predictability, ATC and airplane cockpit workload, ATC coordination procedures, aircraft fuel consumption, flight time, noise, and emissions was the primary focus of this trial.

Nomenclature AAA = Amsterdam Advanced ATC System AAT = Advanced Arrival Techniques ACARS = Airline Communications Addressing and Reporting System ACC = Area Control Center AOC = Airline Operations Control Center ADD = Aircraft-Derived Data APP = Approach Control ATA = Actual Time of Arrival ATC = Air Traffic Control ATM = Air Traffic Management ATO = Actual Time of Fly Over ATS = Air Traffic Services CAS = Calibrated Air Speed CDA = Continuous Descent Arrival COP = Coordination Points DFDR = Digital Flight Data Recorder 1 Manager, Acoustics Technology, Phantom Works, The Boeing Company, 5301 Bolsa Ave. MC H013-B308, Huntington Beach, CA 92647-2099, USA, and Senior AIAA Member. 2 Lead Engineer, Airport Noise Engineering, Boeing Commercial Aircraft, PO Box 3707, MC 67-MK, Seattle, WA 98124-2207, USA 3 Datalink System Engineer, Phantom Works Advanced Air Traffic Management, The Boeing Company, PO Box 3703 MC 8R-79, Seattle, WA 98124-2207, USA 4 Senior Analyst, Operations & Human Factors, BCA Avionics Engineering – ATM, PO Box 3707, MC 07-25, Seattle, WA 98124-2207, USA 5 Concepts Expert, R&D Concepts, Stationsplein Zuid-West 1001, 1117 CV Schiphol-Oost, the Netherlands 6 System Coordinator, Systems Integration and Coordination, Stationsplein Zuid-West 1001, 1117 CV Schiphol-Oost, the Netherlands 7 Expert Airspace & Airports, Airspace & Airports, Stationsplein Zuid-West 1001, 1117 CV Schiphol-Oost, the Netherlands

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6th AIAA Aviation Technology, Integration and Operations Conference (ATIO)25 - 27 September 2006, Wichita, Kansas

AIAA 2006-7753

Copyright © 2006 by The Boeing Company. Published by the American Institute of Aeronautics and Astronautics, Inc., with permission.

EDM = Estimate-Derived Mode ETA = Estimated Time of Arrival ETO = Estimated Time of Fly Over FIR = Flight Information Region FL = Flight Level FMC = Flight Management Computer IAF = Initial Approach Fix IAS = Indicted Air Speed LVNL = Luchtverkeersleiding Nederland MCP = Mode Control Panel MUAC = Maastricht Upper Airspace Center PDM = Parameter-Derived Mode RNAV = Area Navigation ROD = Rate of Descent STAR = Standard Arrival Route TMA = Terminal Maneuvering Area TOD = Top of Descent TP = Trajectory Prediction

I. Introduction evbe

elopments of new concepts and technology for airborne and ground-based systems within aviation have en progressing along different paths and at different paces. On the one hand, automation on the flight deck

has fundamentally changed the way flights are operated. The flight plan produced by the airline’s operations control centre is implemented in the Flight Management System (FMS) and during flight its progress is closely monitored in order to optimize aircraft performance. On the other hand, the ground-based ATC systems focus more and more on achieving a safe, expeditious and orderly flow of traffic by planning available capacity and trying to use it in an optimum manner. To accommodate for differences between planning and execution, ATC declares a lower capacity than can actually be achieved. These "capacity buffers" have become a vital part of the system.

D

Over the years, development work within research organizations has led to the conclusion that further integration of aircraft and ground-based systems within aviation will be the way forward to accommodating larger traffic volumes at major hub airports and en route. Realization of stable traffic streams are a prerequisite to allowing growth of the traffic volume. This will require a flight plan that is common between the aircraft and the ATC that is accurately monitored and adjusted where necessary.

Initiatives for using information from the flight deck to improve the ground system are widespread. However, trying to fully develop all these applications in a single effort would be a huge resource-consuming task with large control risks involved. Thus it is important to start building experience on the subject by focusing on a limited number of applications. This experience will form a foundation for other applications and develop the ability to better judge their capabilities and shortcomings.

Past experience has shown that it is possible to develop and implement a procedure that takes advantage of current technology to maximize the capabilities of current airborne equipment. Through previous demonstrations at different locations throughout the world it was proven that scheduling predictability could be improved, fuel burn is reduced, as well as noise and engine emissions. Two such demonstrations were performed at Louisville1 with the Continuous Descent Arrival (CDA) trial and the Tailored Arrival demonstration in Australia2.

Schiphol airport is a large arrival and departure centre in Amsterdam, Netherlands, and is a prime location to build upon this past experience . In addition, by allowing flights to fly their optimum flight profile during the arrival phase, airlines will be able to save fuel during each arrival and environmental impact of flight operations will be reduced. An optimum flight profile is achieved when the aircraft is allowed to fly a continuous descent at flight idle power setting from Top-of-Descent (TOD) to final approach glideslope intercept. Arrival techniques are considered advanced in this context when integration is used as a means to achieve an improved overall ATM System in terms of environmental impact and efficiency.

The feasibility of elements of the operational concept, such as the status of data link technology, the accuracy of FMS-calculated Estimated Times of Arrival (ETA) at waypoints, the predictability of aircraft-preferred trajectories, and hand-off procedures between different ATC units was investigated in an operational trial. In this trial, the aircraft was able to optimize its vertical profile within specified constraints. On this basis, the aircraft FMS could calculate an airborne flight plan for the execution of the flight profile. The airborne flight plan, including the ETAs,

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was downlinked via the Airline Operations Control Centre (AOC) before the aircraft reached its Top-of Descent. After the execution of the flight, the ETAs were compared with the Actual Time of Arrival (ATA) at those waypoints to determine the accuracy of the predictions. The expected accuracy, based on international trials, was on the order of 6 - 30 seconds. It was important to monitor the repeatability of these types of results to assess their usability for improvement of the ATM system.

In addition, the aircraft-preferred vertical trajectories were monitored. It was expected that, by giving freedom to the aircraft to optimize its descent, the variability of altitudes over waypoints would decrease. This may enable procedural de-confliction of crossing in- and out-bound routes by adding constraints in line with the aircraft-preferred trajectories.

The procedures used during the trial were not new or very different from the current night time procedures. The only noticeable change was the temporary removal of some of the hand-off constraints concerning flight level windows and times in the current procedures. With the gathered data, the current night time procedures would, at a later stage, be optimized based on the experience gained and data collected.

The flight test was an in-service CDA demonstration by subject aircraft of partner airlines passing through Maastricht Upper Airspace Center (MUAC) and LVNL Flight Information Region (FIR) airspace at night en route to Schiphol. These aircraft used the revised CDA procedure developed in the current program during the portion of flight from TOD, which generally occurred in MUAC airspace. Non-CDA aircraft, during the same test period, were considered to be passive subjects since their performance was used for comparison purposes. Other test subjects in the project were MUAC, Area Control Center (ACC), and Approach Control (APP) airspace controllers.

II. Trial Objectives A primary objective of the trial was to determine the operational feasibility of allowing aircraft to perform a

CDA from TOD through LVNL and surrounding centre's’ airspace. A second major objective was to compare the accuracy of time and altitude predictions made by avionics systems in participant aircraft with equivalent predictions made by the Amsterdam Advanced ATC (AAA) ground system with a view to considering how AAA performance might be improved by use of an RNAV procedure and by utilization of aircraft-derived estimates of time and altitude. Subjective data were gathered to gauge controller and flight crew satisfaction with the procedure; inter-facility impact was also assessed. Finally, objective data were gathered to ascertain the level of benefit in terms of reduced environmental impact and reduced operating costs that might be expected compared with current night time operations and with conventional day-time operations. The following assessments were performed to support the objectives: Assessment of predictability of aircraft progress along the 4D flight path

The Advanced Arrival Techniques (AAT) is based to a large extent on the hypothesis that interaction between air- and ground-based systems can significantly improve the performance of the overall ATM System. Therefore, one of the most important aspects explored in the operational trial was to gauge the ability of in-service aircraft to predict a path before TOD and accurately fly this calculated path while conforming to a specified speed profile. Assessment of use of aircraft-derived data to improve the predictability of the ATM system

In addition to the ability of the aircraft to perform the procedure defined, the accuracy of the pre-descent predictions was also assessed to ascertain whether the data might in the future be used to improve predictions made by the ATC ground system to the point where sequencing and merging could be performed based on predictions without significant tactical intervention. Assessment of airlines’ satisfaction with the procedure and operating cost impact

The procedures developed for the trial were aimed at allowing a single flight of a participating airline to fly a CDA from TOD to the runway while causing little or no deviation from current operational practice, and causing minimal operational disturbance. Although this procedure is not intended for operational introduction, airline feedback concerning the level of satisfaction with the procedures and with its impact on operating costs was elicited. Assessment of crew satisfaction with the procedure and workload impact

In the same way that airline satisfaction was assessed, flight crews were asked for feedback on the procedures used during the operational trial. Benefits and shortcomings were assessed. Assessment of controllers’ satisfaction with the procedure and workload impact

In the same way that flight crew satisfaction was assessed, Air Traffic Services (ATS) controllers from the participating units, MUAC, ACC and APP, were asked for feedback on the procedures used during the operational trial. Benefits and shortcomings were assessed.

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Assessment of inter-facility impact The AAT strategy is based on a concept that requires inbound flights to report their planned arrivals paths, lateral

route and altitudes at waypoints, estimated times over waypoints, and speed profile. These data will be used by the ground system to sequence and de-conflict the traffic as necessary by adjusting speed and/or routing for single or multiple flights. These processes will be coordinated and clearances delivered across multiple sectors and facilities in order to implement the sequencing and conflict resolution. Although simple and static coordination procedures are already established, the trial aimed to assess the inter-facility impact of CDA procedures beginning at TOD and continuing to the runway. Assessment of environmental impact

Use of CDA’s to reduce environmental impact is considered to be an effective measure that should be implemented at noise-sensitive airports. For this trial, the environmental impacts in terms of noise and engine exhaust emissions were analyzed.

This paper discusses the results and analyses for the first three and the last objectives of the flight trial. A complete discussion of results of all objectives can be found in the “Evaluation of Schiphol CDA Trials3.” Based on this initial step, LVNL and Boeing ATM strategy R&D group has published a document, “Advanced Arrival Techniques4,” to lay out a strategy for future Schiphol arrival procedures.

III. Trial Procedures During the course of the AAT project, the procedures for the operational trial were collaboratively developed

with all partners, LVNL, Boeing, MUAC, Transavia and Martinair and laid down in a procedure design document5. The guiding principle was to adhere as much as possible to existing procedures and agreements with adjacent centres.

As the CDA trial starts at cruising levels, cooperation from Upper Airspace Units, in this case MUAC, was required. The CDA trial into Amsterdam was operationally supported by MUAC, LVNL, Transavia with their Boeing 737 fleet (B737-700 and 800) and Martinair (with Airbus A320 and McDonnell Douglas MD11). Also Belgocontrol and Reims ACC were informed of the CDA trial.

MUAC’s contribution ensured that aircraft arriving from the east via EELDE or NORKU and from the south via DENUT or HELEN could participate in the trial as seen in Figure 1. To allow CDA’s from TOD down to the landing runway, the only noticeable change was the temporary removal of some of the hand-off procedures at coordination points (COP). Calculated profiles were used as guidance material for the procedure development and communication to controllers. In addition, relevant information on the trial was shared with adjacent centres on a daily basis.

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EHAM

ARTIPROBIS

NORKU

PAM

EEL

DOBAK

KUBAT

SOMPA

TEMLU

BEDUM

RIVER

HELENDENUT

NARIXNIRSI

EH604

EH614

EH608

SOKSI

+FL 060250KIAS+4000 ft

220KIAS

+4000 ft220KIAS

+2900 ft

+3400 ft

+4000 ft220KIAS

Figure 1. Standard lateral routings in FIR from South and Ea

A. Flight Procedures Lateral path

From the ATS routes, aircraft followed the Standard Arrival Routes (STARs) to the Initial Approach Fix (IAF). Within the Terminal Maneuvering Area (TMA), use was made of the so-called night transitions. Night transitions are a published RNAV procedure designed to reduce noise by allowing aircraft below 7,000 feet to fly only in defined corridors and to use minimum thrust. These transitions provided lateral routes from the IAF to either runway 06 or 18R.

Advantage of this routing was that it corresponded to ‘normal’ night time operations. Moreover, these routes must to be adhered to during night operations by Dutch law. The use of standard routings seen in Figure 1 allowed for a predictable lateral flight path. The flight crew could initiate arrival planning at an early stage, i.e. well before TOD.

As a consequence however, the CDA trial was only conducted when the Schiphol night transitions were in force. Use of night transitions is mandatory during night time; they are defined for runway 06 and 18R with some limitations related to incoming aircraft capabilities, weather, or airport and ATC systems services.

Vertical path

Along the standard lateral path, the aircraft was free to optimize its vertical path. The published altitude and speed restrictions at the FIR boundary and the IAF were no longer imposed and were ignored. The published altitude and speed constraints during the last portion of the flight however remained valid to ensure adherence to the night time operation over land. These restrictions included a maximum of 4000ft and maximum of 220 kts at SOKSI and NIRSI, and 3400ft at the Intermediate Fix (IF) that serves as the interception of the ILS 18R or ILS 06 localizer.

The expected vertical path was analysed using the Boeing Climb-Out Performance (BCOP) simulation program. Details of the BCOP program can be found in Annex A of Reference 3. This provided input to the assessment of the impact on transfer conditions from MUAC to ACC and for the hand-over from ACC to APP at the TMA boundary.

Descent speed schedule

In common practice during night time operations, a wide range of descent speeds have been experienced. Therefore it was agreed to set a standard speed schedule for the purpose of the CDA trial. This increased the

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operational predictability for ATC, and avoided situations where aircraft were overtaking on the same lateral path. It was assumed that setting a standard speed schedule would not negatively impact the results of the trial as the speed schedule could be planned before initiating the descent. The agreed speed schedule was:

Mach: FMC default Descent speed: 300kts Below FL100: 250kts NIRSI/SOKSI: 220kts.

B. Flight Crew Procedures The flight crew was informed of the trial procedures by means of pilot briefing forms. The crew was to initiate

the execution of the CDA trial by requesting participation when first transferred to MUAC. The flight crews established the arrival plan before TOD. The flight crew was informed of the runway in use

and, based on the standard routings the lateral profile was implemented in the FMC. Also, the descent speeds were set in the FMC and the constraints at the FIR boundary and the TMA boundary were removed from the FMC flight plan. Subsequently the FMC calculated an idle descent path to the first vertical constraint. At that time, still before TOD, the projected flight plan was logged. To achieve this, Transavia utilized an ACARS CDA downlink which was initiated within five minutes before reaching TOD. The function sent down the calculated flight plan for the descent which includes altitudes, speeds and times over waypoints along the flight path. Martinair utilized a procedure in which the expected times over waypoints were written down by the pilots before TOD.

During the descent, MUAC, ACC and APP endeavoured to allow a continuous descent according to the calculated FMC profile by providing timely descent clearances. The pilot followed the FMC-calculated vertical profile. At any time, either the flight crew or ATC could cancel the CDA based on the actual operational situation, e.g. due to a separation conflict. However, in cases where small deviations from the lateral or vertical path were required for separation purposes, a procedure was implemented that allowed the flight crew to return the aircraft gently to the originally-calculated flight path when separation had been re-established. In case of significant deviations however, the CDA trial was cancelled for that flight.

Specific radio transmission procedures were used for the trial to indicate that the aircraft was participating in the CDA trial. Standard radio communication failure procedures applied.

C. ATC Procedures – MUAC, ACC, and APP For ATC, training bulletins were developed for both LVNL and MUAC operational personnel. Also Quick

Reference Charts were made available at the controllers’ working positions for both ACC and APP control within LVNL. Initiation of CDA trial

At 22.30 local time (LT), the LVNL supervisor contacted the MUAC supervisor with the details of the execution of the CDA trial for that night. The execution of the trial itself, based on visibility, significant weather, the availability of system support and the runway in use, was agreed between the two parties. When requested, MUAC then approved the conduct of the CDA trial for individual flights and facilitated the execution of the CDA trial by providing timely descent clearances. Transfer of control / Transfer of communication

The hand-off instructions between MUAC and ACC and for the ACC to APP hand-off in internal LVNL operational documentation (VDV) remained in force. However, it was recognised that the actual altitudes, speeds and thus the handover points would change significantly in respect to the current instructions (MUAC - ACC) and internal hand-off procedure (ACC - APP). For example, in the case of the EELDE 1A arrival followed by an ARTIP 2A transition for RWY 06, it was expected that the aircraft would enter the FIR at approximately FL 310 and subsequently enter the TMA at FL210. This caused a larger than normal distance between the transfer of communication point at the FIR boundary and IAF respectively and the transfer of control points FL245 and FL095 respectively – see also Figure 2.

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ARTIP EELDE

ACC

APP

FL 210

FL 310FL 295

FL 245

FL 140

FL 095

1500 ft

Figure 2. Typical flight profile for EELDE 1A arrival followed by a ARTIP 2A transition

Execution of CDA trial

ATC (MUAC, ACC and APP) facilitated the execution of the CDA trial by providing timely descent clearances to the aircraft as far as practicable. Other traffic not participating in the CDA trial was handled according to existing night procedures. Therefore the CDA trial was accommodated only as long as traffic conditions permitted. When necessary, the CDA trial was cancelled and additional instructions were provided.

IV. Analysis and Results A variety of data sources were available for the evaluation. The primary sources of data and information were

the airplane and the ground radar system. Data was collected from the Airline Communications Addressing and Reporting System (ACARS), Mode-S surveillance, the Digital Flight Data Recorder (DFDR) and the AAA system.

A detailed description of the data, their sources and definition can be found in Annex C of Reference 3. In addition to the technical data, some objectives such as the subjective evaluations of flight crew, airline, and controller satisfaction were evaluated based on surveys or interviews.

During the period of the CDA trial, a total of 875 flights landed at Schiphol. The total number of transitions that were flown was slightly lower due to several nights with low visibility and high winds as well as a few propeller aircraft that did not fly transitions. See Figure 3 for runway usage during the trial period. From the total number of transition flights, only 490 flights were eligible for the trial, i.e. Transavia B737 or Martinair A320 or MD-11. Out of this total, only 192 flights actually participated in the trial for various reasons, as shown in Table 1. The following sections aim to present the detailed results for several key objective defined in Section II.

Figure 3. Runway usage per night during the trial

Table 1. Summary of flights participating in the CDA trial

Candidate flights Actual CDA flights

Airline actype #

flights actype # flights %flights57%MPH A320 77 A320 44

MPH MD11 14 MD11 3 21%36%TRA B737/8 399 B737/8 14539%Total: 490 192

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A. Assessment of predictability of aircraft progress along the 4D flight path The first objective was to assess the predictability of the flight path. Several observations were made based on

four primary metrics. They include the comparisons of the ATO-ETO time differences, actual and estimated flight levels, actual and estimated IAS, and deviations in the lateral path. Each participating flight was evaluated by visual inspection of the lateral path, vertical profile and the wind profile

Observing the lateral path showed any speed control applied by controllers. Observing the vertical profile provides insight into the vertical path as well as the IAS profile of the flight. The wind profile provides a comparison between the actual winds experienced by the aircraft during its descent and the altitude winds that were used by the FMC when it calculated the downlinked estimates. Through a visual assessment of the degree of deviation aided by auxiliary calculations, an estimate of the wind-error was made. This estimate was then used to remove the wind component effects from the time error assessment. An example wind profile is shown in Figure 4.

Figure 4. Wind speed (left) and direction (right) differences between different sources as a function of FL.

Analysis was performed along four “significant moments”. These were defined as Boundary Entry, Stack

waypoint, Merge point in TMA, and Runway Threshold (DES). The Boundary Entry (BEN) is the entry waypoints EEL, NORKU, HELEN, DENUT. The Stack (STK) waypoints at ARTIP and RIVER, the merge point (MRG) in the TMA at NARIX/NIRSI, SOKSI, and the runway threshold (DES) at EHAM runway 06 or 18 R

Using these four significant moments, segments were defined for analysis. This method permitted detailed analysis of the descent and identification of sources of deviations. The segments were defined as Cruise to BEN, BEN to STK, STK to MRG, and MRG to DES.

The Cruise to BEN segment begins at the moment at which the downlink was initiated by the flight crew. The accuracy of the length of the segment in time was limited due to the unpredictable delay in the ACARS network and the absence of a timestamp in the FMC-originated message. The end point of the segment was defined by the boundary entry point. A segment extending to TOD would have been preferable, but the FMC-downlinked data did not provide estimated data for this waypoint.

The BEN to STK continuing onwards from the previous segment, this segment terminated at the stack. This waypoint was chosen since, from the available waypoints in the downlinked data, it was, although not optimal, the closest one to a significant speed profile change passing FL100.

The STK to MRG segment was introduced to allow assessment of predictability at the merging point in the TMA. The accuracy of the results was limited by a +/- 10 second error margin. This margin stemmed from the fact that the AAA system did not determine actual times for this waypoint. It was not a part of the AAA route. The alternative method of determining the actual time for the merge point has an inherent limitation as mentioned.

The MRG to DES segment terminates at the runway threshold. Note that there is a discrepancy between the definition of the FMC estimate for arrival and the AAA/TWR system’s definition. The former computes to the RWY THR, whereas the later computes to the RWY TDZ. This difference amounts to an average of approximately four seconds which have to be subtracted from the estimate error figures listed in annex F of Reference 3.

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ETO accuracy analysis method

For the purposes of the analysis, two types of ETO accuracies are introduced. The first group is labeled “cumulative accuracies”. This means for instance that if the FMC predicted that the aircraft arrives at the stack 20 seconds too late, this error propagates to the errors from the stack to NIRSI (MRG) as well as from NIRSI to the RWY (DES). The other type of ETO accuracy is called “incremental accuracies” and represents the estimated error for the duration of the segment. This figure facilitates in-depth analysis, for instance to trace where errors are occurring and what their cause could be. Table 2 illustrates ETO-ATO accuracies.

Table 2: Illustration of accuracy errors between estimated Time Of flyover and Actual Time Of flyover

Segment: Incremental error on segment: Cumulative error for segment end: Cruise – BEN 5 5 BEN – STK 12 17 STK – MRG -3 14 MRG – DES 30 44

In order to analyze the factors that influence predictability, their effect on predictability needs to be quantified.

To this end, the ETO accuracy statistics were considered by selectively applying a number of filtering criteria. The primary filtering criterion was the removal of the effect of wind. Since the wind factor had a significant impact on predictability, two sets of statistical data, with further filtering applied, have been created. One set is presented without wind filtering applied along with a second set with the wind effect eliminated from the accuracy numbers.

Given these two sets of accuracy statistics, a number of other sub-sets of flights were subsequently defined in order to identify causes for deviations. Flights were eliminated from the sample for which a level segment was observed, but not including those flights that leveled off against the MCP setting. No re-routing nor level-off against MCP caused exclusion of all flights that performed a re-route after the downlink of the estimate data or which had to level off against their MCP setting at any given point. When the pilot initiates an early descent by selecting “descend now” (B737), it will descend at about 1000feet/min. The use of this feature could be recognized in the vertical profile graphs and was recorded during the off-line evaluation process. The prescribed descent speed for the trial was 300kts IAS from Mach transition to FL100. When a significant deviation from this speed profile was observed in the offline analysis, the deviating pattern was indicated for use by this filter. A speed deviation was considered significant when there was a sustained deviation of ten knots IAS or more.

For the purpose of predictability analysis, flights were designated as “CDA flights” when the ACC controller had marked the flight as a CDA flight by AAA system input and the following condition was also met and during off-line analysis, it was observed that the flight’s routing conformed to the prescribed routing for the trial, the vertical profile showed linear behavior without level-offs against the MCP setting, and the target descent speed adhered to was 300kts IAS between Mach transition and FL100. Figure 5 depicts some results in graphical format for uncorrected and corrected ETO’s.

Figure 5. Graphical presentation of ETO accuracy (average, minimum and maximum difference) at boundary and EHAM for uncorrected and filtered data

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Data validity and accuracy considerations In order to appreciate the level of reliability of the data presented in the analysis in the section above, the

following should be taken into account. The removal of the effect of wind is a manual process where, through visual assessment of the wind pattern and some auxiliary calculations, a correction for wind error caused by inaccuracies in the wind data available to the FMC is derived. The reference data is wind information derived from the Mode-S data of the flight in question; this is not a fully validated method as yet and can be unreliable, especially in aircraft turns. Also wind corrections were determined and applied per segment increments. Particularly for the Cruise – BEN segment, often no wind data from the FMC was available when the flight was navigating directly to either the boundary entry point, some other intermediate waypoint, or the stack waypoint, and the ABM PTS option is not chosen in the FMC. As a result, in those circumstances, the wind data from the route section before the DCT TO waypoint is not downlinked. This leads to cumulative ETO inaccuracies for the other segments from which the wind error for the segment to BEN could not be eliminated. When looking at the accuracies for the MRG point and DES, due account of a few limitations/differences has to be taken.

Since the AAA route does not contain any waypoints after STK, the system does not determine an ATO for the MRG point (i.e. NIRSI/NARIX or SOKSI). Hence MRG point ATO’s were determined from the Mode-S data. The accuracy of this method is limited to +/- 10 seconds. On average, it is expected to result in zero seconds of error, but it will add up to the SD value for this point.

As mentioned earlier, the AAA/TWR systems determined the ETA for EHAM by calculating to the RWY TDZ. The FMC computes to the RWY THR point however. On average, this will cause a +4 seconds error on the MRG – DES segment. This difference needs to be subtracted from the ETO accuracy numbers for EHAM.

Annex F-III in Reference 3 provides summary tables for Flight Level, Speed and TOD-location ranges as reference material in addition to the graphical information in the previous section.

B. Assessment of the Predictability Improvement for the ATM system Improving the predictability of the ATM system can be achieved in two ways which are not mutually exclusive.

Improving the predictability by the aircraft and the predictability of the ground system by the use of aircraft-derived data can be employed partially together.

Assessment of the predictability improvement by the aircraft

Aircraft predictability is dependent on a number of factors. The effects of these factors are derived from the results analysis in the previous section. It is essential that the FMC uses accurate altitude wind information. In the participating aircraft, wind information was usually available down to FL100. Significant winds below this altitude, for instance strong surface winds, result in substantial prediction error. It is recommended, therefore, to include a near surface level wind for use by the FMC in calculating the predictions for intermediate levels. Considering the higher impact of wind error at lower altitudes due to the higher wind/groundspeed ratio, the density of the wind information provided to the FMC should be higher towards ground level. Route deviations from the planned route after a single prediction cause considerable estimation error. In order to enhance predictability, route changes after significant prediction-dependent moments should be avoided whenever possible. Also speed deviations for a considerable amount of time, or significant speed changes for short periods in the descent, result in prediction error.

Assessment of use of aircraft-derived data in enhancing the predictability of the ATM system

The use of Aircraft-Derived Data (ADD) to improve the predictability of ATC-systems is a complex issue. Factors which play a role are use of operational procedures by the flight crew as well as ATC, and the level and modes of integration of ADD and ground systems data. In this section, the subject of use of ADD in ATC systems will be analysed at a high level within the context of the trial experiences and results. An in-depth analysis would be beyond the scope of this paper.

The analysis is structured by considering two possible modes of integrating ADD into ATC system ground processing. For reasons of simplicity, these modes will be described as two independent. The two modes are defined as Estimate-Derived Mode (EDM). In this mode, the estimate data from the FMC will be copied by the ground system without additional processing. This means that estimates for time, level and speed will be used directly by client applications in the ATC system like planning and conflict-detection functionalities. It could be necessary to augment the data by deriving additional information and/or more detailed estimates for other 4D points on the trajectory than those delivered by the downlinked information.

The prime advantage of this mode is that estimate data is derived taking into account all the relevant aircraft-specific parameters which could influence the 4D-path. This potentially provides a solution with a high accuracy. There are some issues associated with the use of this mode. One is the quality of the ADD-based predictions is

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primarily affected by the availability of all the constraints that need to be applied to the aircraft trajectory. These constraints include the ones concerned with de-confliction as well as arrival and, in future concepts, departure planning at the FIR-boundary. It will therefore be necessary to update the FMC with every relevant constraint that needs to be imposed for ATM purposes. Subsequently, the new estimates, based on the latest constraints, would need to be downlinked. This issue requires a robust solution of reliably communicating ATC-restriction-based constraints and tying the results into the ground system. In order to allow the FMC to derive correct estimates, it is imperative that it uses accurate wind information for the 4D-path to be flown. It has been demonstrated that the wind information used by the FMC in the trial flights often contained inaccurate wind estimates resulting in large estimation errors. For this mode, it would be essential therefore to provide the FMS with updated and accurate wind prediction information. The current FMC implementations employ a maximum of three or four wind layers, which inherently limits achievable accuracy. The granularity of the data needs at least be up to the flight plan level, i.e. estimates for each waypoint. For de-confliction purposes, it will probably be necessary for the ATM system to receive estimate data with a higher level of accuracy. This may add significantly to data link requirements. In order for ATC to plan an inbound flight into an arrival stream, the centre will need to be able to modify the arrival plan over one or more waypoints of the route. Using EDM, the FMC becomes part of the calculation algorithm to derive an alternative 4D-profile. This may cause undesirable or even unacceptable delay in the planning activity, impose a high demand on the available data link channel, or result in extra workload for flight crew and/or ATC. As the flight progresses, updates to the original or latest downlinked estimate data will inevitably occur. Criteria need to be defined for resending estimate data based on certain threshold values and/or update frequency. Based on currently-available bandwidth for such a data link application, this could be a significant issue.

Parameter-Derived Mode (PDM) takes ADD at a lower level of detail from the FMC. This means that rather than taking the results of the estimate process of the FMC as the values to use in the ground system, relevant parameters from the FMC, both actual as well as planned, are taken and integrated into the Trajectory Prediction (TP) function of the ground system. Although there are a multitude of different parameters to choose from, specific emphasis should be put on the the IAS-descent, Cruise Mach/CAS, Flight Level constraints, Speed constraints, Actual speeds, Meteorological information, and TOD point.

This mode also has a potential for deriving accurate estimates since the ground system is able to compose and maintain detailed and up-to-date wind information for the airspace through which it is predicting 4D-profiles. Since wind is a predominant element in the accuracy of 4D estimate data, this mode is well-positioned to derive estimates with small error margins. It also makes the planning and de-confliction algorithms independent from the FMC, which provides a more robust solution for air-ground integration.

C. Assessment of airlines’ satisfaction with procedure and operating cost The final results of the time savings and fuel burn analysis are shown in Table 3 for the Martinair MD-11 and in

Table 4 for the Transavia 737NG. As predicted, an optimally flown CDA will lower the fuel burned by eliminating the applied-thrust level segments. Time is also saved due to staying in a cruise speed condition longer.

The principle data for the assessment was derived from the DFDR data collected from the Martinair MD-11’s and Transavia 737NG’s flown into Schiphol Airport during the night time trial period. Data was collected leading up to the trial period to establish a baseline to use for comparison with the CDA. The specific data collected from the DFDR was fuel flow rates per engine and GMT time recorded. The fuel flow rates (lbs/hour) were integrated over the time of descent from fixed locations.

Tables 3 and 4 provide an overview of the results of the operating costs and airline satisfaction assessment. Feedback from the airline representatives in the project team confirms that the numbers are motivating. However, one pilot recalls removing the altitude constraint at, for example, NORKU during actual flight resulted in a 400 lbs fuel burn benefit. Therefore, these numbers may even be pessimistic.

Table 3. MD-11/PW4660 Engines Schiphol CDA Flight Trial Time Savings and Fuel Burn estimates from DFDR Analysis.

Reference 200Nmi From Threshold (Above FL300)

Time (Minutes) Fuel (lbs)

Night time Conventional Arrival 33.9 2545.8 Standard 2K Day time Arrival 32.9 3463.1 Standard 3K Night time Arrival 37.2 3233.5 CDA Arrival 32.5 2406.3

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139.4 Savings of CDA Conventional 1.4 1056.7 Savings of CDA Standard Day time 0.4 827.2 Savings of CDA Standard Night time 4.7

Fuel (lbs) Reference 200Nmi From Threshold (Below FL300)

Time (Minutes)

Night time Conventional Arrival 25.2 1886.5 Standard 2K Day time Arrival 23.4 1889.8 Standard 3K Night time Arrival - - CDA Arrival 22.7 1586.1

300.4 Savings of CDA Conventional 2.5 303.7 Savings of CDA Standard Day time 0.7

Table 4. B737/CFM56 Engines Schiphol CDA Flight Trial Time Savings and Fuel Burn estimates from DFDR Analysis

Reference 100Nmi from Threshold Time (Minutes) Fuel (lbs) Standard 2K Day time Arrival 23.4 760.5 Standard 3K Night time Arrival 23.2 850.4 Conventional Arrival 23.5 816.5 CDA Arrival 23.4 798.1 Savings of CDA Standard Day time -0.2 89.9 Savings of CDA Standard Night time 0.1 56.0 Savings of CDA Conventional 0.0 37.7

D. Assessment of the environmental impact (noise and emission) Reducing environmental impact was a major goal of the AAT project. To assess the environmental impact of the

CDA flight trial, flight data was required from the participating airplanes. Recognizing the importance of this particular objective, both partner airlines, Martinair and Transavia, agreed to provide the data necessary to make the assessment. Several engineering tools were used and some built to generate comparisons between the standard arrival procedures and the CDA procedures as flown by the airlines during the trial. Final results will be used to show some of the many environmental advantages of the CDA procedure.

Boeing uses the FAA Integrated Noise Model (INM) to evaluate airplane noise around airports. The INM is an industry standard for noise assessments though it is not used at Schiphol Airport. A standard metric for airplane operational noise is peak dBA. Peak dBA is the highest A-weighted sound level recorded as an airplane flies overhead. A-weighting is used for airplane noise typically and is an estimate of the measure of annoyance a person feels when they hear a sound. A similar metric is SEL or Sound Exposure Level. This is the dBA as a function of time of airplane overflight and is integrated over the airplane flyover time. This makes it sensitive to an observer’s exposure time and thus to the airplane speed. Using the INM, it is possible to create noise maps, footprints, and contours. These contours can be based on single event flyovers, or on a composite of multiple airplanes over a period of time.

For this study, three gaseous emissions were calculated: oxides of nitrogen (NOx), hydrocarbons (HC), and carbon dioxide (CO2). NOx and HC are the gaseous emissions that are of primary concern for the local air quality around airport communities. The effect on local air quality depends on the mass of pollutant which is emitted into the local atmospheric boundary layer. The height of this layer varies, but for this study it has been assumed to be 3000 feet above ground level. CO2 is an important greenhouse gas which is long-lived in the atmosphere. The total mass of CO2 emitted is of concern for global climate change, but it is not important whether the CO2 is emitted close to the ground or at altitude. Therefore in this study NOx and HC are calculated during only a short portion of the airplane descent, but CO2 production is calculated for the entire descent. Emissions estimates were computed using an emission calculation process developed at Boeing with the assistance of the engine manufacturers. The emissions computation requires the same information used in the noise and fuel burn calculations, such as speed, altitude, time, fuel flow rate and also knowledge of the engine fuel efficiencies, which was provided by the engine manufacturer.

The primary data source for the environmental impact assessment was the DFDR data from the participating airplanes. The data necessary from the DFDR included time, airplane altitude, engine rotation speed, airplane speed,

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airplane location in latitude and longitude, fuel burn rates, among many other parameters that can be used to assist in understanding the behavior of the airplane and assessment of the impact.

The data analysis was performed in several phases. The goal of the analysis was to show that CDAs benefit the environments in which they are performed. Converting the known data set from the DFDR to environmental metrics was achieved.

The initial phase was to collect the data from Martinair and Transavia for the airplanes taking part in the CDA trial. Once the data was collected, it had to be reviewed and compared to a set of assumptions that assisted in defining a baseline day or night procedure, a CDA procedure, or a procedure that did not fit the definition. The criteria were based on visual observation of plotted data. The following gives a detailed description of how each profile was judged and categorized.

Procedure Evaluation Criteria: CDA: • Minimal altitude stabilization or levelling from observed TOD point. • Minimal to no observed increase in thrust from idle until final landing segment. • Speeds consistent with an idle descent path; no excessive use of speed brakes.

Baseline Day: • An observed stabilization or levelling segment at 2000’ over a significant track distance. • Observed thrust level increase corresponding with the 2000’ levelling segment. • Constant speed observed over 2000’ level segment.

Baseline Night: • An observed stabilization or levelling segment at 3000’ over a significant track distance. • Observed thrust level increase corresponding with the 3000’ levelling segment. • Constant speed observed over 3000’ level segment.

Conventional: • No observed or significant stabilization or levelling segment. • Some observed thrust level increases over descent profile.

There were a few observed flights that did not fit into any of the categories. Some had very early TOD points

while others made excessive use of speed brakes or changed speed or thrust level excessively. Figures 6 through 9 show profiles categorized into the four different procedures for the Transavia 737NG flights that participated in the flight trial.

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Figure 6. Recorded and analyzed flight trial profiles from Transavia 737NG DFDR (Baseline Day profiles).

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Figure 7. Recorded and analyzed flight trial profiles from Transavia 737NG DFDR (Baseline Night profiles).

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50Transavia 737NG Conventional Profiles

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Figure 8. Recorded and analyzed flight trial profiles from Transavia 737NG DFDR (Conventional profiles).

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Figure 9. Recorded and analyzed flight trial profiles from Transavia 737NG DFDR (Continuous Descent profiles).

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Once the flights were sorted into the procedure categories, some of the data parameters from the DFDR were used to compute noise and fuel burn estimates. Fuel burn was computed by integrating the fuel flow rate over time from various positions from the runway threshold. The INM was used to generate noise under the flight path and noise contour predictions. Since the INM requires a profile with associated engine thrust, a thrust value had to be computed. Boeing had access to the thrust and engine RPM relationships. These tables were used to derive an engine thrust from the DFDR-recorded N1 engine rotation speed and computed Mach number of the airplane.

Comparisons were made between the CDA procedure sets and the baseline sets. The baseline sets were the Daytime and Night time procedures and the conventional procedure. Noise under the flight path was computed as well as noise contours using the Integrated Noise Model. Emissions data for NOx, CO2, and HC were computed using an emission calculation process developed at Boeing with the assistance of the various Boeing engine manufacturers.

Figures 10 through 13 show the comparison of DFDR-derived noise profiles for the airplane. The profiles selected from the flight trial data sets for these comparisons were observed to be the best flown CDA and the worst case day time and night time standard procedures, as defined in the procedure evaluation criteria. For the noise observed directly under the flight path, the CDA procedure shows a potential of 12dBA improvement over the baseline procedures for the MD-11 and about 9dBA for the 737. Even comparing the Conventional procedure, there is a potential noise improvement of up to 3dBA.

Examining Figure 10 and Figure 13, the noise contours change significantly when flying a CDA procedure compared to a standard procedure. Even though the noise does not change when the airplane is on final approach, the noise that the airplane produces farther from the airport is significantly reduced. Of particular note is the difference in noise energy in day time and night time procedures along the flight track. It is shown here that the high energy closer to the airport during the day is shifted to lower energy noise but over a greater area for the night time procedure. CDA procedures eliminate most of the noise spread over the more distant communities.

Tables 4 and 5 show the emissions calculation results from the flight data for the MD-11 and the 737NG respectively. Negative percentages indicate an emissions reduction from the baseline to the CDA procedure from the baseline flight recorder data sets. A sample of six flights from the flight trial data sets were used to compute a relative order of magnitude for emissions changes resulting from the CDA procedure.

The MD-11 CDA flight data in Table 5 shows the local air quality emissions NOx and HC have a large reduction of up to 70% over the baseline data sets. This is due to elimination of the long level segments where the airplane is flying at increased power and burning a significant amount of fuel at low altitudes. There is a slight increase in the CO2 produced during the entire descent.

Similar trends are shown for the 737NG in Table 6. The main difference can be attributed to the differences in airplane performance between the MD-11 and the 737NG. The 737NG is more modern and much smaller than the MD-11. It is able to fly almost a CDA procedure and control speeds and distances much better than the MD-11 with little intervention from Air Traffic Control. The only significant difference is between the standard night time arrivals. The CDA produces slightly more NOx below 3000 feet. At 3000 feet the airplane is on final approach with a potential level segment before capturing the 3 degree glide slope. The night time profile would have a level segment above 3000 feet altitude whereas the daytime procedure would be below 3000 feet altitude. Under these ideal circumstances, the CDA and the night time profile should be about the same. The particular profiles chosen for the emission analysis show slightly more thrust use at low altitudes for the CDA and therefore an increase in NOx was calculated. This could have been due to pilot corrections for winds, flap and gear deployment time differences, final runway, or any variety of operational reasons.

Overall there is either a neutral or positive reduction of airplane emissions due to CDA procedure. The benefits come from the reduction of thrust applied at low altitudes and the decrease in excess fuel burned during step down arrivals.

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Figure 10. Noise under the Flight Path for the Martinair MD-11 procedures comparison from CDA flight trial data.

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Figure 11. Noise under the Flight Path for the Transavia 737NG procedures comparison from CDA flight trial data.

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Standard Daytime Arrival 737NG - ARTIP2B

Standard Nighttime Arrival 737NG - ARTIP2B

Continuous Descent Arrival 737NG - ARTIP2B

Figure 12. Transavia 737NG DFDR derived Noise Contours comparing CDA and Standard Arrivals for ARTIP2B.

Standard Daytime Arrival MD11 - ARTIP2B

Standard Nighttime Arrival MD11 - ARTIP2B

Continuous Descent Arrival MD11 - ARTIP2B

Figure 13. Martinair MD-11 DFDR derived Noise Contours comparing CDA and Standard Arrivals for ARTIP2B (Note: the contours show calculated data plotted along a night transition route, which not necessarily indicates a route that is actually flown).

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Table 5. MD-11/PW4660 Engines Schiphol CDA Flight Trial Emissions estimates from DFDR Analysis.

MD-11/PW4062 Engines From 3000' feet Altitude and

below From 200NMI from Threshold

Emissions NOx (kg) HC (kg) CO2 (lbs) Standard 2K Daytime Arrival 3.42 16.16 7559.0 Standard 3K Nighttime Arrival 3.31 16.01 7508.9 CDA Arrival 1.06 4.98 7917.9 Saving of CDA over Standard Daytime -69% -69% +5%

Saving of CDA over Standard Nighttime -68% -68% +5%

Table 6. B737/CFM56 Engines Schiphol CDA Flight Trial Emissions estimates from DFDR Analysis

737NG/CFM56-7B

From 3000' feet Altitude and below

From 100NMI from Threshold

Emissions NOx (kg) HC (kg) CO2 (lbs) Standard 2K Daytime Arrival 1.79 0.154 3300.8 Standard 3K Nighttime Arrival 0.88 0.159 2999.8 CDA Arrival 1.06 0.139 2943.0 Saving of CDA over Standard Daytime -41% -9% -11%

Saving of CDA over Standard Nighttime +20% -12% -2%

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V. Conclusion By keeping the trial simple in design and executing it during periods with low traffic density, it was possible to

collect a large amount of data. This contributed to the overall conclusion that the trial can be considered a success. Aircraft-derived data has the potential to be used for improving predictability of complex operations such as CDA, but there is still a lot to be learned before an operational concept that utilises these features can be adopted in high density airspace. Environmental benefits were shown by analysis of the flight tracks, and of engine and aircraft configuration data. Cooperation among all operational partners ensured that all relevant aspects of flying CDA’s could be examined and learned from.

Significant analysis has been performed on the data obtained during the trial of which the results are presented in this report. However, the extensive scope of what can be learned from the data has not yet been exploited to the fullest. This awareness demonstrates the enormous potential for the future ATM-system of air-ground integration and the need and effectiveness of trials which seek to explore it.

Accuracy of aircraft-predicted Flight Levels is, on average, within 300ft with a standard deviation less than 600 ft. Average values for estimated times are also good at less than 10 seconds at waypoints and 25 seconds at destination. However, significant standard deviation exists at 25 seconds for waypoints and up to 40 seconds at the destination. Accurate wind and temperature information, the former particularly at the lower altitudes, should improve predictability for both the air and the ground. However, there is a wide variance of other parameters (e.g. procedure design and FMC behaviour in coping with altitude and speed constraints, auto-flight modes, and pilot techniques) that influence predictability and their influence is not understood to the full extent. Modern aircraft are eminently capable of conforming to defined lateral routes to a high degree of accuracy. However, certified accuracy RNP only includes flight technical error, and pilots must fly the defined procedures in order to meet the performance requirements. Night time CDAs should include entering descent wind and temperature forecasts prior to TOD. Automated uplink capability is available on most aircraft to allow this. Further research, supported by future trials, should be carried out to validate the conclusions drawn concerning the impact on predictability of wind velocity and outside air temperature inaccuracies in FMC assumptions, and on the recommended methods of ameliorating the resulting errors. Future trials should contain clearer explanations of the purpose of the trials, and the need to follow procedures completely. Guidance on desired level of conformance with pilot-controllable parameters should also be given. Finally, future procedures, both trials and operational, should include guidance on aircraft reconfiguration timing.

In terms of the improvement for the ATM system, the results show that aircraft-derived data is significantly better than present AAA-derived data and can potentially be used to improve predictability. Possible applications of aircraft-derived data lie in the areas of FIR boundary arrival management, sequencing by Area Control, merging streams in the TMA, use of better weather data and optimization of transfer points. In addition, it can be concluded that aircraft-derived data (ADD) can contribute significantly to the predictability of the ATM System and will be required to achieve a major leap forward in current day trajectory prediction system development. Integration of ADD into ground-based ATM-systems involves a complex design process in which a diversity of engineering issues need to be resolved such as data link use, reliability of ground and airborne system data, human factors issues, operational procedures, etc. Analysis of the accuracy and behavior of ADD obtained in an operational context such as a trial is imperative to foster the engineering processes as mentioned above.

Operating cost impact for airlines significantly depends on the costs related to fuel. Participating airlines have indicated that the savings are worthwhile, but that CDA’s should primarily be focused on alleviating the noise on the ground. For the noise calculated directly under the flight path, the CDA procedure showed a potential of 12dBA improvement over the baseline procedures for the MD-11 and about 9dBA for the 737. Even comparing the Conventional procedure, there is a potential noise improvement of up to 3dBA. The resulting emissions reductions calculated from the airplane flight recorder data showed a neutral to positive change for both airplane types.

Future trials will and should focus on further improvements and enhancements to airplane flight path repeatability for predictability needed in the ATM system. With increased use of CDA's worldwide, the experience gained from this trial will assist in improving ATM and airplane systems for far reaching benefits to other airports and to the global environment.

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Acknowledgments This project was joint program between the LVNL and Boeing with additional participants from the airlines and

the NLR. These are the people that made this project such a great success. Boeing – Daniel McGregor, Belur Shivashankara, Al Withers, Mike Garrison, Louis Bailey, Yuqiang Wu and in memory to our colleague Cathy Davis LVNL - Evert Esterveld, Suzanne Noordam-Bolding, Gerhard Nijenhuis, Hans Peter Spies, Bart Thissen, Henry Dwarswaard and other participating controllers Martinair - Ruud Bakker, Jeffrey Tofohr Transavia - Franklin van der Staaij, Iwan van Ree NLR - Rob Ruigrok

References 1Clarke, J.P., et al., “Development, Design, and Flight Test Evaluation of a Continuous Descent Approach Procedure for

Nighttime Operation at Louisville International Airport,” Report No. PARTNER-COE-2005-02, January 9, 2006. 2Rober, C. J., “Tailored Arrival Phase 1 Report,” ATC Datalink News, June 26, 2005, URL:

http://members.optusnet.com.au/~cjr/TAP.htm3Kok, B. B., et al., “Research report - Evaluation of Schiphol CDA trials,” LVNL Document R&D 06/009 version 1.0, 14

July 2006 4Kok, B. B., et al., “Research report - Advanced Arrival Techniques,” LVNL Document R&D 05/026 version 2.0, 31 July

2006 5Kok, B. B., et al., “Procedure Design Document Advanced Arrival Trial procedures,” LVNL Document R-140 issue 1.2, 8

December 2005.

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