Episode 3 D FTS on 4D trajectory management and complexity reduction - Experimental Plan EPISODE 3

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1 EPISODE 3 Single European Sky Implementation support through Validation Document information Programme Sixth framework programme Priority 1.4 Aeronautics and Space Project title Episode 3 Project N Project Coordinator EUROCONTROL Experimental Centre Deliverable Name FTS on 4D trajectory management and Deliverable ID D Version 1.01 Owner Cyril Allignol DSNA Contributing partners DSNA - Page 2 of 22 -

2 Approval DOCUMENT CONTROL Role Organisation Name Document owner DSNA Cyril Allignol Technical approver NATS Adrian Clark Quality approver EUROCONTROL Ludovic Legros Project coordinator EUROCONTROL Philippe Leplae Version history Version Date Status Author(s) Justification - Could be a reference to a review form or a comment sheet /02/2009 Approved DSNA Approval of the document by the EP3 Consortium /03/2009 Approved Catherine Palazo Format changes - Page 3 of 22 -

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4 TABLE OF CONTENTS 1 EXECUTIVE SUMMARY INTRODUCTION PURPOSE OF THE DOCUMENT INTENDED AUDIENCE BACKGROUND ORGANISATION OF THE DOCUMENT REFERENCES APPLICABLE DOCUMENTS OTHER DOCUMENTS EXERCISE SCOPE AND JUSTIFICATION STAKEHOLDERS AND THEIR EXPECTATIONS DESCRIPTION OF ATM CONCEPT BEING ADDRESSED High level objectives Specific objectives CHOICE OF INDICATORS AND METRICS EXERCISE Assumptions Airspace Information Traffic Information Equipment scenario requirements EQUIPMENT REQUIRED TO CONDUCT THE EXERCISE PLANNING AND MANAGEMENT ACTIVITIES RESOURCES TIME PLANNING RISKS ANALYSIS SPECIFICATION DATA COLLECTION METHODS ANALYSIS METHOD DATA LOGGING REQUIREMENTS OUTLINE REPORTING PLANS DETAILED EXERCISE DESIGN VARIABLES ASSUMPTIONS LENGTH AND NUMBER OF RUNS TIME PLANNING FOR THE EXERCISE ACRONYMS Page 5 of 22 -

5 LIST OF TABLES Table 4-1 Stakeholder expectations Table 4-2: Operational improvement steps Table 4-3: KPAs and Focus Areas Table 5-1 Expected effort Table 5-2 Risk identification Table 7-1 Number of planned runs Table 7-2 Detailed time planning Page 6 of 22 -

6 1 EXECUTIVE SUMMARY This document describes the work to be carried out conducting a fast-time simulation that tests a method to allocate takeoff times, which may lead to de-complexified en-route traffic, WP These fast-time simulations are part of the Single European Sky Support through Validation Project Episode 3 (EP3). They belong to EP3 WP 4.3, whose goal is to validate technologies, processes and procedures related to the en-route area of the execution phase. This exercise will specifically: Assess the feasibility of the method, i.e. show whether an appropriate allocation of takeoff times is likely to reduce complexity; Provide initial trends regarding efficiency and capacity. The methodology employed is to use an optimisation algorithm to allocate takeoff times to aircraft from a simulated 2020 reference day of traffic. Results will be expressed as trade-offs between delays and complexity measurements. - Page 7 of 22 -

7 2 INTRODUCTION 2.1 PURPOSE OF THE DOCUMENT This document provides the Validation Exercise Plan for EP3 WP4.3.2 FTS on 4D trajectory management and complexity reduction. 2.2 INTENDED AUDIENCE The intended audience includes: EP3 WP4: En route and traffic management: o EP3 WP4.1 WP4 management and co-ordination leader o EP3 WP4.2.1 Validation strategy and support leader o EP3 WP4.3 WP4 validation activities leader EP3 WP2: System consistency EP3 WP4 expert group and FTS partners. 2.3 BACKGROUND The EPISODE 3 project validation strategy focuses more on establishing consistency of validation process and ensuring that the necessary enablers are in place to allow the effective, concept focussed validation activity which must take place at the operational domain, EP3 WP3, WP4 & WP5. The validation activity is reflected through the following goals: Establish an understanding of SESAR Target Concept within the operational segment for which the WP is responsible. Identify validation activities and objectives based on existing research and best expert opinion on relevance for SESAR, to include: o o o a clear orientation towards objective data collection within the performance framework including the identification where possible of local targets; provision of detail on key elements of the target concept; and identification of issues of importance to the further development of the concept. From these basic goals, the EP3 WP4 has derived a specific validation strategy for the work package. It provides the necessary link between the SESAR Concept of Operations and the validation activities in this project. The methodology is based on E-OCVM (European Operational Concept Validation Methodology) Steps 0 and 1. This en route validation strategy describes an approach illustrating how the ATM Target Concept could be assessed and validated in terms of concept refinement and some selected performance areas. The problem statement and the proposed solutions are derived from SESAR deliverables D1 and D2 and detailed in the relevant Detailed Operational Descriptions. They are expressed in terms of Lines of Change and Operational Improvement steps. A first mapping and scoping of the envisaged validation exercises towards the Lines of Change and the Operational Improvement steps has been done. - Page 8 of 22 -

8 As SESAR follows a performance-oriented strategy, the targets are set in terms of Key Performance Areas. A more detailed breakdown defines the Focus Areas and the associated Key Performance Indicators. The contribution of this validation strategy towards the focus areas is provided. Finally, the validation tools and techniques for each exercise are defined. An expert group will provide clarification on SESAR concepts to support exercise leaders or to resolve aspects of the SESAR ConOps (concept of operations) where there is a lack of common understanding. The fast-time simulation exercise described in this document is the EP3 WP 4.3.2, FTS on 4D trajectory management and complexity reduction. 2.4 ORGANISATION OF THE DOCUMENT The document is structured in four main parts. The first details the scope, justification and objectives of the exercise together with the methodology, indicators and metrics, hypotheses and scenarios tested; The second part describes the activities, resources and time planning; The third part describes the data collection and analysis methodology; and Finally the fourth part details the exercise design. - Page 9 of 22 -

9 3 REFERENCES 3.1 APPLICABLE DOCUMENTS [1] EP3 Proposal - Episode3 DoW [2] E-OCVM - E-OCVM Version 2.0 [3] E3-WP2-D RQT - Performance Framework cycle 1 [4] SESAR initial DOD M2 - Medium-Short Term Network Planning [5] SESAR initial DOD E6 - Conflict Management in En-Route Operations [6] DLM SESAR D2: Air Transport Framework, The Performance Target [7] RPT The SESAR Performance Booklet [8] DLM SESAR D3: The ATM Target Concept [9] DLT SESAR Concept of Operations [10] DLM SESAR D4: ATM Deployment Sequence [11] SESAR Performance Assessment Task Report Capacity and Quality of Service - Version June OTHER DOCUMENTS [12] SESAR D1 The Current Situation - Approved & Accepted [13] SESAR Performance Objectives and Targets RPT Draft [14] EUROCONTROL: Study Report Challenges to Growth, EUROCONTROL, Version 1.0, [15] EUROCONTROL: Long-Term Forecast Flight Movements Version 1.0, Page 10 of 22 -

10 4 EXERCISE SCOPE AND JUSTIFICATION 4.1 STAKEHOLDERS AND THEIR EXPECTATIONS The table below shows the main stakeholders needs and expectations from a reduction of complexity for en-route traffic. Stakeholder External / Internal Involvement EP3 WP4.4 Internal - Consolidation of performance and operational results - Reporting of consolidated results for WP4 EP3 WP2.4.1 Internal - Provide traffic data for the simulations Why it matters to stakeholder - Knowledge of the effect of optimised takeoff time allocation on complexity, safety and delays for en-route traffic. - Compatibility of the method with traffic forecast for En-route ATC External N/A - Reduced complexity for enroute sectors will lead to ability for the en-route ATC to easily handle the growing traffic. Airlines External N/A - Reduced complexity will enable ATC to handle more traffic to better accommodate the airlines demand ANSP External / Internal Represented by DSNA as exercise leader - Acceptance by the human actors (ATCOs). Table 4-1 Stakeholder expectations Performance expectations Trade-offs between solved conflicts (complexity) and delays Recommendations for changes to the DODs. N/A Evaluation of the possible de-confliction for en-route traffic (achievable ratio of solved conflicts) Trade-offs between deconfliction ratio and induced delays Trade-offs between solved conflicts (complexity) and delays. 4.2 DESCRIPTION OF ATM CONCEPT BEING ADDRESSED This validation exercise addresses specifically the following element of the SESAR ConOps (SESAR D3): Significantly reducing the need for controller tactical intervention by reducing the number of potential conflicts, using a de-confliction method. The aim is to provide the Network Manager with a new delay allocation method, which would take into account the structure of the traffic rather than macroscopic measurements such as sectors capacity. This table below shows the list of OI steps that will be addressed by the exercise using Fast Time Simulation techniques: - Page 11 of 22 -

11 OI Id OI Title OI Step Id OI Step Title OI Step Description OI Step Rationale IP IOC/FOC How addressed? L04-01 Improving Network Capacity Management Process DCB Short Term ATFCM Measures In order to close the gap between ATC and ATFCM, operational procedures are developed requiring dynamic coordination between more than one ACC, the AOs and the CFMU The rigid application of ATFM regulations based on standard capacity thresholds as the predominant tactical capacity measure needs to be replaced by a closed working relationship between ANSPs/FMP and CFMU, which would monitor both the real demand, the effective capacity of sectors having taken into account the complexity of expected traffic situation. IP1 2010/2014 This exercise will test a new method for takeoff time allocation, thus try to enhance the current short term network capacity management. - Page 12 of 22 -

12 OI Id OI Title OI Step Id OI Step Title OI Step Description OI Step Rationale IP IOC/FOC How addressed? L03-03 Planning the Shared Business Trajectory (SBT) AUO Agreed Reference Business / Mission Trajectory (RBT) through Collaborative Flight Planning Airspace users can refine the SBT in a number of iterations taking into account constraints arising from new and more accurate information. They access an up-to-date picture of the traffic situation with the level of detail required for planning. The collaborative planning process terminates when the RBT is published. The RBT continues to evolve in order to reflect all the applicable clearances and constraints and in accordance with the applicable trajectory change rules. At any time it is the reference used by all ATM partners during flight execution. IP2 2016/2021 The takeoff time allocation process is likely to lead to updates of the RBT until departure time. Table 4-2: Operational improvement steps The applicable DODs for this exercise are M2 (Medium/Short term network planning [4]) and E6 (Conflict management in en-route operations [5]). The M2 focuses on the operating principles relevant to the medium/short term planning phase for: Network management; Airspace management; Airspace user operations, when interacting with the network management function. In particular, this exercise addresses section 4.4 in M2: Network Support to Balance Planned Demand and Capacity. The E6 addresses the following system improvements: - Page 13 of 22 -

13 Safety: support tools and automation to maintain or reduce operator s task load by improving their situational awareness, minimising last-minute tactical and supporting routine task load, as well as decreasing complexity perception; Flight efficiency: aircraft fly their optimum profiles to the maximum extent possible through the RBT; Capacity: operators are supported by advanced automation capabilities that enable efficient and timely tactical intervention when required and ensure that clearances have a longer valid duration; Flexibility: users decide how to face disruptions and unexpected constraints on resources. This exercise addresses section 4.1 in E6: En-Route Support to De-Conflict and Separate Traffic. SESAR has defined a set of 11 Key Performance Areas (KPAs), and within each area a set of Focus Areas (FA) focussing on well defined understandable subjects. The table below summarises the relevant KPAs and Focus Areas covered by the Exercise: SESAR KPA CAPACITY SAFETY Description This KPA addresses the ability of the ATM system to cope with air traffic demand in number and distribution through time and space. It relates to the throughput of that volume per unit of time, for a given safety level. This KPA addresses the risk, the prevention and the occurrence and mitigation of air traffic accidents. Focus Area FA-1 Airspace Capacity FA-3 Network Capacity FA-1 ATMrelated safety outcome Table 4-3: KPAs and Focus Areas Description This Focus Area covers the capacity of any individual or aggregated airspace volume within the European airspace. Is concerned with overall network throughput, taking into account the network effect of the airspace and airport capacity in function of traffic demand patterns. This Focus Area covers the occurrence and prevention of accidents involving aircraft with a MTOW>2.25 tons, operating under IFR, with a direct and/or indirect ATM contribution. This includes collisions on the ground and in the air High level objectives This validation exercise is part of the first step of the study of SESAR concept. This exercise examines whether selected political goals set by SESAR may theoretically be achievable by adjusting the departure time of aircraft in the ECAC zone. The aim is to make the en-route traffic easier to handle by the controller: as the current enroute sectors will be overloaded in a 2020 environment, one way to reduce the controller workload is to have traffic with no conflict, or at least with fewer conflicts. This exercise though tests a new method for applying delays, different from the CFMU method. This new method is be based on the microscopic structure of the traffic (the intersections between aircraft trajectories) rather than on the macroscopic criteria (sector capacity) used by the CFMU current algorithm. A shift on take off times is likely to reduce potential en-route conflicts. - Page 14 of 22 -

14 4.2.2 Specific objectives The political goals of SESAR foresee that the target system should enable a three-fold increase in capacity, which will also reduce delays, both on the ground and in the air. The target system should also improve the safety performance by a factor of 10. No study has yet demonstrated that these high level goals are achievable at network level given credible airline demand and airport infrastructure development in the future. This validation exercise examines to what extent these goals are theoretically achievable simply by adequately adjusting the departure time of aircraft and using more precise information on aircraft trajectories available in the SESAR planning phase. The objectives of this exercise can be expressed as follows: Propose and study an algorithm to execute ATFM slot allocation, when 4D flight plans are provided. Evaluate the workload reduction that can be obtained according to the time dispersion allowed for takeoffs. More in details, this exercise determines whether an appropriated allocation of takeoff times is likely to reduce the number of potential conflicts for the en-route phase. The fast-time simulations provide: Feasibility information: is it possible to solve all potential conflicts or only part of them? Trade-offs between the percentage of solved conflicts and the delays associated (e.g. how much delay will be necessary for solving all conflicts, 80% of conflicts, or how much conflicts are we able to solve with a maximum delay per aircraft of 15 minutes, 10 minutes, ). For each simulation, departure delay for each aircraft is measured, as well as the amount of remaining conflicts. These data provide mean delay, percentage of delayed aircraft and percentage of solved conflicts, which are used to produce trade-off diagrams. 4.3 CHOICE OF INDICATORS AND METRICS The exercise provides initial trade-offs between takeoff time delays and complexity reduction. The indicators that will be selected to describe complexity mainly take into account the number of potential conflicts remaining after solving and the number of aircraft in each sector, as well as the traffic that will enter a sector for the next 10 minutes. The exact metric is not yet defined, as the convergence of the algorithms used to optimize the traffic is closely linked to it. The optimisation algorithm tries to minimize a cost function, which is directly linked to the complexity metric we choose; the convergence of the algorithm, and thus the achievement of a solution, is strongly dependent on the cost function. The most probable metric (proved to have lead to good solutions on small instances) will be simply the number of remaining conflicts for the en-route phase. 4.4 EXERCISE A series of fast-time simulations will be carried out on the traffic samples (2006 and 2020 traffic) provided by EUROCONTROL. For each sample, simulations will be carried out with both standard routes and direct routes (depending on the performance of the algorithms, an area restriction might be necessary). The simulations can be described as the following steps: - Page 15 of 22 -

15 Generating aircraft trajectories from initial demand, using CATS/OPAS simulator; Computing all 3D crossings between the above trajectories; Compute the takeoff times, so as to ensure that there is no loss of separation at the above 3D crossings; Re-input these takeoff times in CATS/OPAS to verify the solution Assumptions The main assumptions made for this exercise are: Aircraft Equipment All aircraft are supposed to be equally equipped with a precise enough FMS system; that means: each aircraft is able to follow a defined trajectory in x, y, z and t to the limit measurable in the simulation. Optimisation parameters The only variable parameters for the optimisation (de-confliction/de-complexification) are the takeoff time of each aircraft. Thus each aircraft flies its preferred (though optimal) trajectory. However, the global performance of the network is not be optimal, since lots of parameters would enable to enhance the quality of the allocation (e.g. flight level allocation, route allocation, etc). Data handling The algorithm used is not able to handle an entire day of traffic since the amount of data is huge. To get round this problem, the data is handled by the use of a sliding window method. This means that the algorithm: Optimises (and allocate takeoff times) a T w minutes wide slice (or window) of the day of traffic; Fixes the takeoff times for aircraft departing in the first δ minutes of the window; Slides the window δ minutes ahead; Starts again at step until the end of day is reached. This method enables to handle greater amount of traffic. The downside is that the allocation costs more in terms of delays than if the data was handled at once. T w and δ will be adjusted to the performance of the optimisation algorithm. Typical values are 20 minutes for T w and 5 minutes for δ. Iterations per Scenario In order to achieve a statistical confidence on the simulation results, suitable scenarios using some stochastic resolution method (i.e. a method that includes some random operations) will be run an appropriate number of iterations. Indeed, two solutions issued from two different runs, with the same set of parameters, might differ. However, considering the huge data dimension, the differences are limited regarding the optimized metric. It is also possible to reproduce exactly a simulation that was already run. Wind and weather modelling Wind and weather conditions are not taken into account for the simulations. - Page 16 of 22 -

16 4.4.2 Airspace Information The analysis shall be ECAC-wide. However, there may be a need to reduce the geographical scope due to the limitations of large-scale fast-time simulations. Sectorisation and route structure will be today s. Two types of simulations will be carried out: Aircraft following standard routes, Aircraft following direct routes from their origin to their destination airports Traffic Information The reference traffic corresponds to 18 th, 21 st and 23 rd of July The 2020 scenarios are built from the reference scenarios by applying the expected traffic growths provided by the EUROCONTROL Statistics and Forecast Service (STATFOR). This traffic is issued by EP3 WP Equipment scenario requirements For the objectives of EP3 WP4.3.2, no need has been identified so far for updating the platform as it is now. 4.5 EQUIPMENT REQUIRED TO CONDUCT THE EXERCISE The CATS/OPAS simulator has been selected to carry out the EP3 WP4.3.2 FTS. CATS/OPAS is used to generate the trajectories from the initial demand. It is then used to verify that the calculated takeoff times indeed reduce complexity, and to provide several information and statistics, mainly concerning sectors capacity. 5 PLANNING AND MANAGEMENT 5.1 ACTIVITIES The main activities that are necessary to perform this validation exercise are: Preparatory activities: o o Definition of the exercise, including selection of the SESAR CONOPS elements, platform, scenarios. The main output of this activity is the present document (D Experimental Plan); The input data pre-processing (generating traffic from initial demand, computing potential conflicts, etc.). The execution activities that include: o o Validation of scenarios; Simulation execution; Post-exercise activities: o o Analysis of the results; Elaboration of final report (document D : Simulation Report). - Page 17 of 22 -

17 5.2 RESOURCES To perform this validation activity, the following skills are required from the participants: Understanding of the operational concept addressed. Knowledge of FTS tools, in particular CATS/OPAS simulator. Experience in data analysis. The following table shows the expected effort in person weeks to perform all activities described in the previous section: Effort (pw) Activities Detail DSNA PREPARATORY EXECUTION POST-EXERCISE Exercise Definition 1 Input data pre-processing 3 Validation of Scenarios 1 Simulation Execution 2 Output data post-processing 1 Results analysis 5 Final Report 2 TOTAL (pw) 15 Table 5-1 Expected effort 5.3 TIME PLANNING The exercise began in September 2008 with the selection of the set of OIs and the Performance Indicators. The exercise conduction is planned to start at the end of January 2009, and to end in March The exercise report is planned for April RISKS Risk <1>: Description: Validation of Hypothesis and Assumptions by the Airport Expert Group It may be the case that the Expert Group discusses some hypothesis on this exercise late for their implementation for the simulations. Impacted Area: Own Exercise Other Exercise WP Level: Low Medium High Possibility of occurrence: Low Medium High Contingency Actions Mitigation Actions: Responsible party: Ask the experts directly N/A. WP4 - Page 18 of 22 -

18 Risk <2>: Description: Algorithm performance It may be the case that the algorithms we plan to use are not efficient enough to handle such a huge amount of traffic data. Impacted Area: Own Exercise Other Exercise WP Level: Low Medium High Possibility of occurrence: Low Medium High Contingency Actions Mitigation Actions: Responsible party: N/A In this case, a restraint area will be substituted to the ECAC wide zone. WP4.3.2 Table 5-2 Risk identification 6 ANALYSIS SPECIFICATION 6.1 DATA COLLECTION METHODS The simulations tool will provide quantitative data regarding traffic trajectories and number of residual conflicts, as well as information regarding traffic in en-route sectors that be used to provide complexity measurements. 6.2 ANALYSIS METHOD Quantitative analysis will be carried out to reach a specific numerical result, often with an associated statistical level of confidence. Some post-processing activities may be carried on (depending on the parameters of the algorithm) in order to compute the complexity indicators. The analysis and reporting activities include: Description of the trade-offs between delays and residual conflicts for the different validation simulations; Preparation of the simulation report. We consider that a reasonable level of confidence is reached if the standard deviation is low enough. 6.3 DATA LOGGING REQUIREMENTS The following is a list of data that will be available, for each run: Number of flights; Number of remaining conflicts; Number of conflicts before optimisation; Departure delay per aircraft; - Page 19 of 22 -

19 Number of delayed flights; Computation time. From this data, we will extract the following trade-offs: Number of flights vs. number of conflicts (before optimisation); Number of flights vs. percentage of delayed flights; Number of flights vs. total amount of delays; Percentage of solved conflicts vs. total amount of delays; Number of aircraft vs. computation time. 6.4 OUTLINE REPORTING PLANS The exercise will provide recommendations for changes to the EP3 DODs. In particular, section 4.4 in M2 and section in E6 are in scope of this exercise. The Simulation Report will be delivered in April The format of this report will be that provided by EP3 WP2. 7 DETAILED EXERCISE DESIGN 7.1 VARIABLES For each sample of traffic considered, two types of simulations are carried out: standard routes simulation, direct routes simulation. The variables for each simulation are takeoff time for each aircraft. 7.2 ASSUMPTIONS For the resolution, the experiment considers no uncertainty with respect to departure time. The robustness of the solutions will be assessed afterwards, and no counter measure is tested in the scope of this exercise. 7.3 LENGTH AND NUMBER OF RUNS For each simulation, a number of runs with the selected traffic sample are conducted. Indeed, it could be needed carrying out more than one simulation run, namely when a stochastic resolution algorithm is used, in order to obtain a statistical mean that could reflect what can be achieved with such a method. This is because the solutions, in the use of a stochastic algorithm, can be very dependent on the elementary steps followed, which are randomly determined. If the experiment obtain similar results for the chosen metrics after a few runs (e.g. 10 runs with the same parameters), then the experiment can be confident that this reflects what an appropriate allocation should be. Should a deterministic algorithm be used (if it is proved to be more efficient), only one run will be needed for each set of parameters. The simulations that will be carried out are: - Page 20 of 22 -

20 For 2006 traffic: 18 th, 21 st and 23 rd of July 2006 in both standard and direct routes; For 2020 traffic: three days of traffic, based on the three previous ones (see section 4.4.3), also in standard and direct routes. The table below gives the planned number of runs for each configuration. If the level of confidence is not met for a given configuration, more runs will be carried out. Note that this table only applies in the case when the stochastic method we plan to use is sufficient enough. In any other case (namely: use of a deterministic method), there will be only one run per configuration. Day of traffic Runs in standard routes Runs in direct routes 07/18/ /21/ /23/ # # # Total runs Table 7-1 Number of planned runs Total runs 7.4 TIME PLANNING FOR THE EXERCISE Activity Write experimental plan Prepare scenarios Run scenarios Write analysis report Week Table 7-2 Detailed time planning - Page 21 of 22 -

21 8 ACRONYMS 3D/4D 3 Dimensional / 4 Dimensional ACC Air Traffic Control Center ANSP Air Navigation Service Provider AO Airline Operator ATC Air Traffic Control ATCO Air Traffic Controller ATFCM Air Traffic Flow and Capacity Management ATFM Air Traffic Flow Management ATM Air Traffic Management CATS/OPAS Complete Air Traffic Simulator / Outils de Planification ATM et de Simulation CFMU Central Flow Management Unit ConOps Concept of Operations DOD Detailed Operational Description DoW Description of Work DSNA Direction des Services de la Navigation Aérienne ECAC European Civil Aviation Conference EEC EUROCONTROL Experimental Center E-OCVM European Operational Concept Validation Methodology EP3 Episode 3 FA Focus Area FMS Flight Management System FTS Fast Time Simulation ICAO International Civil Aviation Organisation IFR Instrumental Flight Rules KPA Key Performance Area MTOW Maximum Take Off Weight NATS National Air Traffic Services NOP Network Operations Plan OI Operational Improvement RBT Reference Business Trajectory SBT Shared Business Trajectory SESAR Single European Sky ATM Research and Development Programme STATFOR EUROCONTROL Statistics and Forecast Service WP Work Package - Page 22 of 22 -

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