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E3-WP2-D2.4.1-04a-TEC-V2.00-diagrams2

Episode 3

D2.4.1-04a - Influence Diagrams Update - Annex to EP3 Performance Framework

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Issued by the Episode 3 consortium for the Episode 3 project co-funded by the European Commission and Episode 3 consortium.

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° 037106

Project Coordinator EUROCONTROL Experimental Centre

Deliverable Name Influence Diagrams Update - Annex to EP3 Performance Framework

Deliverable ID D2.4.1-04a

Version 2.01

Owner

Martijn Koolloos ISDEFE

Contributing partners

AENA, ATMB, CAST, DFS, DSNA, ERC, ISA, ISDEFE, NATS.

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DOCUMENT CONTROL

Approval

Role Organisation Name

Document owner ISDEFE Martijn Koolloos

Technical approver EUROCONTROL Giuseppe Murgese

Quality approver EUROCONTROL Frédérique Sénéchal

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

1.00 30/03/2009 Approved Mark Scott Approval of the document by the Episode 3 Consortium.

2.00 21/07/2009 Approved Mark Scott Update following the continuation and completion of the Influence Modelling Study.

Approval of the document by the Episode 3 Consortium.

2.01 09/11/2009 Approved Catherine Palazo Minor format changes

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TABLE OF CONTENTS

EXECUTIVE SUMMARY......................................................................................................... 11

1 INTRODUCTION ............................................................................................................. 12 1.1 PURPOSE OF THE DOCUMENT ..................................................................................... 12 1.2 INTENDED AUDIENCE.................................................................................................. 12 1.3 DOCUMENT STRUCTURE ............................................................................................. 12 1.4 BACKGROUND............................................................................................................ 12 1.5 GLOSSARY OF TERMS................................................................................................. 13

1.5.1 Definitions ........................................................................................................ 13 1.5.2 Acronyms......................................................................................................... 15

1.6 DEFINITION OF THE EP3 INFLUENCE MODEL................................................................ 16 2 METHODOLOGY ............................................................................................................ 17

2.1 INTRODUCING THE METHODOLOGY .............................................................................. 17 2.2 MODEL NOTATION ...................................................................................................... 17

2.2.1 Model hierarchy ............................................................................................... 20 2.2.2 Variable information – integrated documentation............................................ 20

3 OVERVIEW OF THE INTEGRATED DIAGRAM ............................................................ 21 3.1 COMMON VARIABLES.................................................................................................. 21

3.1.1 OI Steps ........................................................................................................... 22 3.1.2 Indexes ............................................................................................................ 22 3.1.3 Read Input Data module.................................................................................. 22

4 CAPACITY ...................................................................................................................... 23 4.1 AIRSPACE CAPACITY .................................................................................................. 23 4.2 EN-ROUTE CAPACITY ................................................................................................. 24

4.2.1 En-route Planning: Network capacity configuration......................................... 24 4.2.2 En-route Situational Factors ............................................................................ 25 4.2.3 En-route Structural Elements........................................................................... 28 4.2.4 En-route Tactical workload .............................................................................. 28 4.2.5 Variables set by predictability constraint ......................................................... 31 4.2.6 Example Results of the Airspace Capacity Model........................................... 32

4.3 TERMINAL AIRSPACE CAPACITY .................................................................................. 32 4.3.1 TMA Planning: Network capacity configuration ............................................... 32 4.3.2 TMA Situational Factors .................................................................................. 33 4.3.3 TMA Structural Elements................................................................................. 36 4.3.4 TMA Tactical workload .................................................................................... 36 4.3.5 Variables set by predictability constraint ......................................................... 39

4.4 AIRPORT CAPACITY .................................................................................................... 40 4.4.1 Runway Infrastructure...................................................................................... 41 4.4.2 Runway Use..................................................................................................... 41 4.4.3 Impact of Low visibility conditions on runway .................................................. 44 4.4.4 Apron information ............................................................................................ 45 4.4.5 Impact of Low Visibility conditions on Apron ................................................... 46 4.4.6 Use of taxiway system ..................................................................................... 47 4.4.7 Impact of Low Visibility conditions on Taxiway................................................ 48 4.4.8 Example Results of the Airport Capacity Model .............................................. 48

4.5 NETWORK CAPACITY .................................................................................................. 50 4.5.1 En-route Service provision resources.............................................................. 51 4.5.2 En-route Airspace availability .......................................................................... 52

5 EFFICIENCY ................................................................................................................... 53 5.1 FUEL EFFICIENCY ....................................................................................................... 53

5.1.1 Airport Fuel Efficiency Modules ....................................................................... 54

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5.1.2 TMA Fuel Efficiency......................................................................................... 57 5.1.3 En-route Fuel Efficiency................................................................................... 65 5.1.4 Results of the Model ........................................................................................ 68

5.2 TIME EFFICIENCY ....................................................................................................... 71 5.2.1 Taxi-out ............................................................................................................ 73 5.2.2 Taxi-in .............................................................................................................. 74 5.2.3 En-route ........................................................................................................... 74 5.2.4 TMA Arrival ...................................................................................................... 75 5.2.5 TMA Departure ................................................................................................ 76 5.2.6 Results of the Model ........................................................................................ 76

5.3 MISSION-EFFECTIVENESS ........................................................................................... 80 6 PREDICTABILITY ........................................................................................................... 81

6.1 KNOCK-ON EFFECT..................................................................................................... 81 6.1.1 Arrival variability............................................................................................... 82 6.1.2 Turnaround performance ................................................................................. 82 6.1.3 Results of the Model ........................................................................................ 82

6.2 ON-TIME OPERATION .................................................................................................. 86 6.2.1 ATM variability (pre off-block) .......................................................................... 87 6.2.2 ATM assistance in recovering from reactionary delays................................... 88 6.2.3 Airspace User Trajectory Conformance .......................................................... 89 6.2.4 Accuracy of weather forecast .......................................................................... 89

6.3 SERVICE DISRUPTION EFFECT ..................................................................................... 90 7 ENVIRONMENT .............................................................................................................. 91

7.1 LOCAL AIR QUALITY ................................................................................................... 91 7.1.1 Emissions related to thrust (PM, NOx, HC, CO).............................................. 92 7.1.2 Emission Indices.............................................................................................. 92 7.1.3 Emissions directly proportional to fuel burn..................................................... 93

7.2 GLOBAL EMISSIONS .................................................................................................... 94 7.2.1 Avoidance of air masses.................................................................................. 95 7.2.2 Emissions related to thrust (PM, NOx, HC, CO).............................................. 96 7.2.3 Emissions directly proportional to fuel burn..................................................... 97 7.2.4 Results of the model ........................................................................................ 97

7.3 NOISE ....................................................................................................................... 99 7.3.2 Airport configuration....................................................................................... 101 7.3.3 Departure Flight Characteristics .................................................................... 101 7.3.4 Arrival Flight Characteristics .......................................................................... 102

8 FLEXIBILITY ................................................................................................................. 103 8.1 FLEXIBLE ACCESS FOR NON SCHEDULED FLIGHTS ...................................................... 103 8.2 BT UPDATE FLEXIBILITY ............................................................................................ 103

8.2.1 Capacity & headroom .................................................................................... 104 8.2.2 Flexibility to adjust capacity ........................................................................... 104 8.2.3 Traffic forecast & inaccuracies ...................................................................... 104 8.2.4 Accommodated demand................................................................................ 105 8.2.5 Demand variability/sensitivity......................................................................... 105 8.2.6 Airport flexibility.............................................................................................. 105 8.2.7 Business trajectory change request .............................................................. 106 8.2.8 Schedule flight time performance .................................................................. 106

8.3 SUSTAINABILITY FOR MILITARY REQUIREMENTS .......................................................... 107 8.4 SERVICE LOCATION FLEXIBILITY ................................................................................ 107

9 SAFETY......................................................................................................................... 108 9.1 GENERIC OVERVIEW OF IRP MODELLING APPROACH .................................................. 109 9.2 MID-AIR COLLISION................................................................................................... 109

9.2.1 Demand/capacity balancing........................................................................... 110 9.2.2 Sector planning.............................................................................................. 112 9.2.3 Conflict management..................................................................................... 112

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9.2.4 ATC collision avoidance ................................................................................ 114 9.2.5 Airborne collision avoidance.......................................................................... 115

9.3 CONTROLLED FLIGHT INTO TERRAIN .......................................................................... 116 9.3.1 ATC procedures............................................................................................. 116 9.3.2 On-board monitoring...................................................................................... 117 9.3.3 Terrain avoidance warnings........................................................................... 118

9.4 WAKE TURBULENCE ACCIDENT.................................................................................. 118 9.4.1 Conflict prevention ......................................................................................... 119 9.4.2 Tactical wake separation ............................................................................... 120 9.4.3 Wake suppression ......................................................................................... 121 9.4.4 Wake avoidance warnings............................................................................. 121 9.4.5 Wake turbulence survivability ........................................................................ 121

9.5 RUNWAY COLLISION ................................................................................................. 122 9.5.1 Demand/capacity balancing........................................................................... 122 9.5.2 Runway/taxiway configuration ....................................................................... 122 9.5.3 Incursion prevention ...................................................................................... 123 9.5.4 ATC recovery ................................................................................................. 124 9.5.5 Pilot/driver recovery ....................................................................................... 125

9.6 TAXIWAY COLLISION ................................................................................................. 126 9.6.1 Demand/capacity balancing........................................................................... 126 9.6.2 Taxiway configuration .................................................................................... 127 9.6.3 Taxi route deconfliction.................................................................................. 127 9.6.4 Tactical deconfliction ..................................................................................... 128 9.6.5 ATC recovery ................................................................................................. 129 9.6.6 Pilot/driver recovery ....................................................................................... 129

9.7 OTHER ACCIDENT-RELATED PIS ................................................................................ 130 9.8 OTHER INCIDENT-RELATED PIS ................................................................................. 130

10 COST-EFFECTIVENESS.............................................................................................. 132 10.1 OVERVIEW ............................................................................................................... 132 10.2 COMPOSITE FLIGHT-HOURS ..................................................................................... 133 10.3 FINANCIAL COST-EFFECTIVENESS ............................................................................ 133

10.3.1 Staff costs ...................................................................................................... 135 10.4 COST OF ATFM DELAYS .......................................................................................... 136 10.5 COST OF FLIGHT INEFFICIENCY ................................................................................. 137

11 WAY FORWARD........................................................................................................... 138 11.1 SHORT-TERM IMPROVEMENTS TO QUANTIFIED FOCUS AREAS...................................... 138

12 REFERENCES .............................................................................................................. 140

A DECISION ITEMS ......................................................................................................... 141

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LIST OF TABLES TABLE 2-1: NOTATION (AS USED IN ANALYTICA 4.1)............................................................... 18 TABLE 2-2: INFLUENCE ARROWS (AS USED IN ANALYTICA 4.1)................................................ 19

LIST OF FIGURES FIGURE 2-1: EXAMPLE INFLUENCE MODEL WITH VARIABLES NOT QUANTIFIED ON THE LEFT-HAND

SIDE 19 FIGURE 3-1: TOP-LEVEL VIEW OF THE INTEGRATED INFLUENCE DIAGRAM (VERSION 3.0) ........... 21 FIGURE 4-1: AIRSPACE CAPACITY INFLUENCE DIAGRAM.......................................................... 23 FIGURE 4-2: EN-ROUTE NETWORK CAPACITY CONFIGURATION MODULE .................................... 24 FIGURE 4-3: EN-ROUTE QUALITY OF PLANNED DEMAND INFO.................................................... 24 FIGURE 4-4: CONFIGURABILITY/FLEXIBILITY OF EN-ROUTE CAPACITY MODULE .......................... 25 FIGURE 4-5: EN-ROUTE: SITUATIONAL FACTORS MODULE........................................................ 25 FIGURE 4-6: EN-ROUTE QUALITY OF REAL TIME DEMAND INFORMATION MODULE ....................... 26 FIGURE 4-7: EN-ROUTE TRAFFIC COMPLEXITY (3D) MODULE.................................................... 26 FIGURE 4-8: EN-ROUTE TRAFFIC LOAD SMOOTHNESS/OPTIMISATION (TIME) MODULE ................. 27 FIGURE 4-9: EN-ROUTE STRUCTURAL ELEMENTS MODULE ...................................................... 28 FIGURE 4-10: EN-ROUTE TACTICAL WORKLOAD..................................................................... 28 FIGURE 4-11: EN-ROUTE DECISION MAKING MODULE ............................................................. 29 FIGURE 4-12: EN-ROUTE SITUATIONAL AWARENESS AND MONITORING MODULE ...................... 30 FIGURE 4-13: EN-ROUTE EXECUTION MODULE ...................................................................... 30 FIGURE 4-14: VARIABLES SET BY PREDICTABILITY CONSTRAINT ............................................. 31 FIGURE 4-15: AIRSPACE SECTOR HOURLY CAPACITY FOR A “HIGHLY COMPLEX” SECTOR ........ 32 FIGURE 4-16: TMA NETWORK CAPACITY CONFIGURATION MODULE ........................................ 32 FIGURE 4-17: TMA QUALITY OF PLANNED DEMAND INFO MODULE........................................... 33 FIGURE 4-18: CONFIGURABILITY/FLEXIBILITY OF TMA CAPACITY MODULE............................... 33 FIGURE 4-19: TMA SITUATIONAL FACTORS MODULE ............................................................. 34 FIGURE 4-20: TMA QUALITY OF REAL TIME DEMAND INFORMATION......................................... 34 FIGURE 4-21: TMA TRAFFIC COMPLEXITY (3D) MODULE........................................................ 34 FIGURE 4-22: TMA TRAFFIC LOAD SMOOTHNESS/OPTIMISATION (TIME) MODULE ..................... 35 FIGURE 4-23: TMA STRUCTURAL ELEMENTS MODULE........................................................... 36 FIGURE 4-24: TMA TACTICAL WORKLOAD MODULE ............................................................... 36 FIGURE 4-25: TMA DECISION MAKING MODULE ..................................................................... 37 FIGURE 4-26: TMA SITUATIONAL AWARENESS AND MONITORING MODULE .............................. 38 FIGURE 4-27: TMA EXECUTION MODULE .............................................................................. 38 FIGURE 4-28: VARIABLES SET BY PREDICTABILITY CONSTRAINT ............................................. 39 FIGURE 4-29: AIRPORT CAPACITY INFLUENCE DIAGRAM......................................................... 40 FIGURE 4-30: RUNWAY INFRASTRUCTURE MODULE ............................................................... 41 FIGURE 4-31: RUNWAY USE MODULE.................................................................................... 41 FIGURE 4-32: OI STEPS CONTRIBUTING TO RUNWAY OCCUPANCY TIME .................................. 42 FIGURE 4-33: OI STEPS CONTRIBUTING TO SEQUENCING ....................................................... 42 FIGURE 4-34: OI STEPS CONTRIBUTING TO SPACING ............................................................. 43 FIGURE 4-35: OI STEPS CONTRIBUTING TO USE OF RUNWAYS ................................................ 43 FIGURE 4-36: IMPACT OF LOW VISIBILITY CONDITIONS ON RUNWAY CAPACITY MODULE ............ 44 FIGURE 4-37: OI STEPS INFLUENCING THE IMPACT OF LOW VISIBILITY CONDITIONS ON RUNWAY

CAPACITY 44 FIGURE 4-38: APRON INFORMATION MODULE ........................................................................ 45 FIGURE 4-39: STAND PERFORMANCE MODULE ...................................................................... 45 FIGURE 4-40: IMPACT OF LOW VISIBILITY CONDITIONS ON APRON MODULE .............................. 46 FIGURE 4-41: OI STEPS INFLUENCING THE IMPACT OF LOW VISIBILITY CONDITIONS ON APRON

CAPACITY 46 FIGURE 4-42: USE OF TAXIWAY SYSTEM MODULE .................................................................. 47 FIGURE 4-43: IMPACT OF LOW VISIBILITY CONDITIONS ON TAXIWAY MODULE ........................... 48 FIGURE 4-44: OI STEPS INFLUENCING THE IMPACT OF LOW VISIBILITY CONDITIONS ON TAXIWAY

CAPACITY 48 FIGURE 4-45: CAPACITY AT AN AIRPORT WITH PARALLEL INDEPENDENT RUNWAYS .................. 49

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FIGURE 4-46: NETWORK CAPACITY INFLUENCE DIAGRAM....................................................... 50 FIGURE 4-47: OI STEPS INFLUENCING NETWORK CAPACITY ................................................... 51 FIGURE 4-48: EN-ROUTE SERVICE PROVISION RESOURCES MODULE ...................................... 51 FIGURE 4-49: EN-ROUTE AIRSPACE AVAILABILITY MODULE..................................................... 52 FIGURE 5-1: FUEL EFFICIENCY MODEL (TOP LEVEL) ................................................................. 53 FIGURE 5-2: ON STAND FUEL BURN ........................................................................................ 54 FIGURE 5-3: TAXI-OUT FUEL BURN.......................................................................................... 55 FIGURE 5-4: TAXI-IN FUEL BURN............................................................................................. 56 FIGURE 5-5: LANDING ROLL OUT ............................................................................................ 56 FIGURE 5-6: FUEL EFFICIENCY AT THE AIRPORT ...................................................................... 57 FIGURE 5-7: EFFICIENCY OF TMA OPERATIONS ON DEPARTURE .............................................. 57 FIGURE 5-8: DEPARTURE PROCEDURES ................................................................................. 58 FIGURE 5-9: OI STEPS INFLUENCING DEPARTURE ROUTES ...................................................... 58 FIGURE 5-10: OI STEPS INFLUENCING AIRSPACE STRUCTURE................................................ 58 FIGURE 5-11: OI STEPS INFLUENCING SEQUENCING.............................................................. 59 FIGURE 5-12: OI STEPS INFLUENCING SPACING .................................................................... 60 FIGURE 5-13: EFFICIENCY OF TMA OPERATIONS ON ARRIVAL................................................ 60 FIGURE 5-14: OI STEPS INFLUENCING AIRBORNE QUEUING .................................................... 61 FIGURE 5-15: ARRIVAL PROCEDURES ................................................................................... 62 FIGURE 5-16: OI STEPS INFLUENCING INTERRUPTED DESCENTS ............................................ 62 FIGURE 5-17: OI STEPS INFLUENCING SEQUENCING .............................................................. 63 FIGURE 5-18: OI STEPS INFLUENCING SPACING..................................................................... 64 FIGURE 5-19: OI STEPS INFLUENCING ARRIVAL ROUTES ........................................................ 64 FIGURE 5-20: OI STEPS INFLUENCING METEO....................................................................... 64 FIGURE 5-21: OI STEPS INFLUENCING AIRSPACE STRUCTURE................................................ 65 FIGURE 5-22: FUEL EFFICIENCY IN THE TMA ........................................................................ 65 FIGURE 5-23: EN-ROUTE FUEL EFFICIENCY MODULE.............................................................. 66 FIGURE 5-24: EXTENSION DUE TO EN-ROUTE DESIGN ........................................................... 67 FIGURE 5-25: EXTENSION DUE TO ROUTE UTILISATION .......................................................... 67 FIGURE 5-26: EXTENSION DUE TO ATC ROUTING.................................................................. 68 FIGURE 5-27: EN-ROUTE FUEL EFFICIENCY ........................................................................... 68 FIGURE 5-28: FUEL CONSUMPTION PER FLIGHT..................................................................... 69 FIGURE 5-29: % CHANGE IN FUEL CONSUMPTION PER FLIGHT FROM 2005 VALUE (EXAMPLE

OUTPUT) 70 FIGURE 5-30: SENSITIVITY ANALYSIS OF FUEL CONSUMED PER FLIGHT ................................... 70 FIGURE 5-31: TOTAL FUEL CONSUMPTION IN KILOGRAMS....................................................... 71 FIGURE 5-32: TIME EFFICIENCY FOCUS AREA (TOP LEVEL) ..................................................... 72 FIGURE 5-33: TAXI-OUT ....................................................................................................... 73 FIGURE 5-34: TAXI-IN .......................................................................................................... 74 FIGURE 5-35: EN-ROUTE ..................................................................................................... 75 FIGURE 5-36: TMA ARRIVAL DURATION ................................................................................ 75 FIGURE 5-37: TMA DEPARTURE DURATION........................................................................... 76 FIGURE 5-38: TOTAL FLIGHT DURATION ................................................................................ 77 FIGURE 5-39: SENSITIVITY ANALYSIS OF TOTAL FLIGHT DURATION.......................................... 78 FIGURE 5-40: AVERAGE DEPARTURE DELAY PER FLIGHT........................................................ 79 FIGURE 5-41: IMPORTANCE ANALYSIS FOR TOTAL TAKE OFF DELAY ........................................ 79 FIGURE 5-42: MISSION EFFECTIVENESS................................................................................ 80 FIGURE 6-1: KNOCK-ON EFFECT INFLUENCE DIAGRAM ............................................................. 81 FIGURE 6-2: ARRIVAL VARIABILITY.......................................................................................... 82 FIGURE 6-3: TURNAROUND PERFORMANCE............................................................................. 82 FIGURE 6-4: REACTIONARY DELAYS ....................................................................................... 83 FIGURE 6-5: SENSITIVITY ANALYSIS OF REACTIONARY DELAYS ................................................. 84 FIGURE 6-6: NUMBER OF CANCELLATIONS CAUSED BY LATE ARRIVALS ..................................... 84 FIGURE 6-7: SENSITIVITY ANALYSIS OF NUMBER OF CANCELLATIONS ........................................ 85 FIGURE 6-8: AIRCRAFT READY TO PUSH BACK DELAY............................................................... 85 FIGURE 6-9: IMPORTANCE ANALYSIS FOR READY TO PUSH BACK DELAYS .................................. 86 FIGURE 6-10: ON-TIME OPERATION INFLUENCE DIAGRAM....................................................... 86

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FIGURE 6-11: ATM VARIABILITY (PRE OFF-BLOCK) ................................................................ 87 FIGURE 6-12: LATE NOTIFICATION OF ATM CONSTRAINTS MODULE ........................................ 88 FIGURE 6-13: ATM ASSISTANCE IN RECOVERING FROM REACTIONARY DELAYS ....................... 88 FIGURE 6-14: AIRSPACE USER TRAJECTORY CONFORMANCE ................................................. 89 FIGURE 6-15: ACCURACY OF WEATHER FORECAST................................................................ 89 FIGURE 6-16: SERVICE DISRUPTION EFFECTS ....................................................................... 90 FIGURE 7-1: LOCAL AIR QUALITY (TOP LEVEL) ......................................................................... 91 FIGURE 7-2: COMMON VARIABLES IN THE LOCAL AIR QUALITY INFLUENCE DIAGRAM ................... 92 FIGURE 7-3: EMISSIONS RELATED TO THRUST SETTING............................................................ 92 FIGURE 7-4: EMISSION INDICES.............................................................................................. 92 FIGURE 7-5: EMISSIONS DIRECTLY PROPORTIONAL TO FUEL BURNT.......................................... 93 FIGURE 7-6: GLOBAL EMISSIONS INFLUENCE DIAGRAM (TOP LEVEL) ......................................... 94 FIGURE 7-7: AVOIDANCE OF SUSCEPTIBLE AIR MASSES ........................................................... 95 FIGURE 7-8: GLOBAL EMISSIONS RELATED TO THRUST IN THE TMA AND EN-ROUTE .................. 96 FIGURE 7-9: GLOBAL EMISSIONS DIRECTLY PROPORTIONAL TO FUEL BURNT ............................. 97 FIGURE 7-10: AVERAGE CO2 EMITTED PER FLIGHT................................................................ 98 FIGURE 7-11: NOISE FOCUS AREA (TOP LEVEL)..................................................................... 99 FIGURE 7-12: DEPARTURE ROUTES...................................................................................... 99 FIGURE 7-13: ARRIVAL ROUTES ......................................................................................... 100 FIGURE 7-14: FLIGHT PROCEDURES AND TECHNIQUES ........................................................ 100 FIGURE 7-15: AIRPORT CONFIGURATION............................................................................. 101 FIGURE 7-16: DEPARTURE FLIGHT CHARACTERISTICS ......................................................... 101 FIGURE 7-17: ARRIVAL FLIGHT CHARACTERISTICS ............................................................... 102 FIGURE 8-1: FLEXIBLE ACCESS FOR NON SCHEDULED FLIGHTS DIAGRAM ................................ 103 FIGURE 8-2: BT UPDATE FLEXIBILITY DIAGRAM...................................................................... 103 FIGURE 8-3: CAPACITY AND HEADROOM MODULE .................................................................. 104 FIGURE 8-4: FLEXIBILITY TO ADJUST CAPACITY MODULE ........................................................ 104 FIGURE 8-5: TRAFFIC FORECAST AND INACCURACIES MODULE ............................................... 105 FIGURE 8-6: ACCOMMODATED DEMAND MODULE................................................................... 105 FIGURE 8-7: DEMAND VARIABILITY/SENSITIVITY MODULE........................................................ 105 FIGURE 8-8: AIRPORT FLEXIBILITY MODULE........................................................................... 106 FIGURE 8-9: BT CHANGE REQUEST MODULE ......................................................................... 106 FIGURE 8-10: SCHEDULE FLIGHT TIME PERFORMANCE MODULE ........................................... 106 FIGURE 8-11: SUSTAINABILITY FOR MILITARY REQUIREMENTS INFLUENCE DIAGRAM .............. 107 FIGURE 9-1: ATM-RELATED SAFETY DIAGRAM ...................................................................... 108 FIGURE 9-2: MID-AIR COLLISION MODULE.............................................................................. 109 FIGURE 9-3 SWISS CHEESE MODEL (FROM EUROCONTROL, 2008)................................... 110 FIGURE 9-4: DEMAND/CAPACITY BALANCING ......................................................................... 111 FIGURE 9-5: TRAJECTORY DECONFLICTION........................................................................... 112 FIGURE 9-6: TACTICAL DECONFLICTION ................................................................................ 114 FIGURE 9-7: ATC RECOVERY............................................................................................... 115 FIGURE 9-8: PILOT RECOVERY ............................................................................................. 115 FIGURE 9-9: CFIT MODULE.................................................................................................. 116 FIGURE 9-10: ATC PROCEDURES....................................................................................... 117 FIGURE 9-11: ON-BOARD MONITORING ............................................................................... 118 FIGURE 9-12: TERRAIN AVOIDANCE WARNINGS ................................................................... 118 FIGURE 9-13: WAKE TURBULENCE ACCIDENT MODULE......................................................... 119 FIGURE 9-14: CONFLICT PREVENTION ................................................................................ 120 FIGURE 9-15: TACTICAL WAKE SEPARATION........................................................................ 121 FIGURE 9-16: WAKE AVOIDANCE WARNINGS ....................................................................... 121 FIGURE 9-17: RUNWAY COLLISION MODULE ........................................................................ 122 FIGURE 9-18: RUNWAY/TAXIWAY CONFIGURATION .............................................................. 123 FIGURE 9-19: INCURSION PREVENTION ............................................................................... 124 FIGURE 9-20: ATC RECOVERY........................................................................................... 125 FIGURE 9-21: PILOT/DRIVER RECOVERY ............................................................................. 125 FIGURE 9-22: TAXIWAY COLLISION MODULE ........................................................................ 126 FIGURE 9-23: DEMAND/CAPACITY BALANCING ..................................................................... 127

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FIGURE 9-24: TAXIWAY CONFIGURATION ............................................................................ 127 FIGURE 9-25: TAXI ROUTE DECONFLICTION......................................................................... 128 FIGURE 9-26: TACTICAL DECONFLICTION ............................................................................ 128 FIGURE 9-27: ATC RECOVERY........................................................................................... 129 FIGURE 9-28: PILOT/DRIVER RECOVERY ............................................................................. 129 FIGURE 9-29: OTHER ACCIDENT-RELATED PERFORMANCE INDICATORS ................................ 130 FIGURE 9-30: INCIDENT-RELATED PERFORMANCE INDICATORS............................................. 131 FIGURE 10-1: COST-EFFECTIVENESS INFLUENCE DIAGRAM .................................................. 132 FIGURE 10-2: COMPOSITE FLIGHT-HOURS .......................................................................... 133 FIGURE 10-3: FINANCIAL COST-EFFECTIVENESS.................................................................. 134 FIGURE 10-4: STAFF COSTS............................................................................................... 135 FIGURE 10-5: ATCO COSTS .............................................................................................. 135 FIGURE 10-6: COST OF ATFM DELAYS............................................................................... 136 FIGURE 10-7: COST OF FLIGHT INEFFICIENCY...................................................................... 137 FIGURE 11-1: ARRIVAL TMA FUEL EFFICIENCY INFLUENCE MODEL ....................................... 139

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EXECUTIVE SUMMARY

The focus of this work is to develop a methodology and a model that will allow future ECAC wide performance assessment of the potential performance benefits of the SESAR concept in 2013 and 2020 corresponding to the SESAR Implementation Packages (IP1 and IP2). The methodology follows the structure of Key Performance Areas and focus areas that are defined in D2.4.1-04 Performance Framework.

This document provides a detailed description of the individual influence diagrams, the variables that are included and how the influence models fit together. The document also includes the key decisions taken during the development of the Influence diagrams and the Influence model.

The development of Version 3.0 of the work has captured six key performance areas and seventeen related focus areas integrated into one influence diagram.

One of the key objectives of the modelling of the influence diagrams for the EP3 Influence Model study is to ensure that the model is agile and flexible, transparent and that it allows the complete integration of the diagrams into a single environment.

To meet these objectives and ensure consistency in the model, a number of variables that are used throughout the integrated diagram are defined as common variables.

The following Key Performance Areas and related focus areas have been developed into quantified influence models:

• Efficiency KPA:

o Fuel Efficiency;

o Time Efficiency.

• Environment KPA:

o Global Emissions has been partially quantified.

• Predictability KPA:

o Knock-on Effect.

• Capacity KPA:

o Airport Capacity;

o Airspace Capacity.

The remaining focus areas that are defined in D2.4.1-04 Performance Framework are developed to the level of an influence diagram, but are not quantified.

The data in the model is based, to a large extent, on expert judgement and is for illustrative purposes only. Using such data shows the validity of using influence models to assess the performance of the ATM system; however improved data is required to increase the accuracy and reliability of the results of the influence model.

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1 INTRODUCTION

1.1 PURPOSE OF THE DOCUMENT

This document, D2.4.1-04a, is the Influence Diagrams Update - Annex to EP3 Performance Framework.

The documentation of the influence model that has been developed for Episode 3 WP2.4.1 consists of three documents:

• D2.4.1-04a, Influence Diagrams Update - Annex to EP3 Performance Framework: this document, which provides a detailed description of the individual influence diagrams, the variables that are included and how the influence models fit together. The document also includes the key decisions taken during the development of the Influence diagrams and the Influence model (See Annex A Decision items).

• D2.4.1-04c, User Manual for the Influence Model - Annex to EP3 Performance Framework: provides a description of the requirements for using the model, in terms of hardware and software and high-level instructions for running the model.

• D2.4.1-04e, Influence Model Study - Final Report: describes how the model has been developed, its current status and what actions would be required to make further progress with the model.

1.2 INTENDED AUDIENCE

The intended audience for this document is the same as for the Performance Framework, and includes:

• EP3 partners;

• SESAR community.

1.3 DOCUMENT STRUCTURE

This document is structured as follows:

Section 2 – Methodology: the methodology used to develop the model and the model notation.

Section 3 – Overview of the integrated diagram: the key performance areas covered and a description of the other modules in the top-level diagram.

Sections 4-10 – Key Performance Area descriptions: descriptions of the diagrams within each Key Performance Area.

Section 11 – Way Forward: a summary of the improvements to the model that could be undertaken in the short-term.

Section 12 – References.

Annex A – Decision Items: the key decisions taken during the development of the Influence diagrams and the Influence model.

1.4 BACKGROUND

Episode 3 (EP3) is charged with beginning the validation of the operational concept expressed by SESAR Task 2.2 and consolidated in SESAR Deliverable D3 [3]. The emphasis is on obtaining a system level assessment of the concept’s ability to deliver the defined

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performance benefits in 2013 and 2020 corresponding to the SESAR Implementation Packages (IP1 and IP2).

Future validation exercises within EP3, or future work within the SJU, should provide evidence; studies, simulation results or expert judgement to describe the ability of some aspects of the concept to deliver on some aspects of the performance targets.

These validation exercises could help to populate the EP3 influence model later, and the influence model could subsequently provide an ECAC-wide assessment of performance and support the decision to conduct further exercises or to revise priorities.

1.5 GLOSSARY OF TERMS

1.5.1 Definitions

Term Definition

Airport, TMA, En-route ECAC Performance Indicator

The Airport, TMA, En-route ECAC layer are a sub part of the ECAC wide Performance Indicator. They address the ECAC wide performance of all Airports, TMA and En-route of an OI or a group of OIs. For example, this can be the influence of group of OIs on the fuel consumption for all the ECAC airports.

Airport A defined area on land or water (including buildings, installations and equipment) intended to be used either wholly or in part for the arrival, departure and surface movement of aircraft.1

ATM Network Airspace structure (airport nodes linked together by airspace volumes e.g. sectors and routes) and technical infrastructure network (aircraft, ground systems, communication network, etc…) supporting the management of air traffic.

ECAC Performance Indicator The ECAC wide Performance Indicator layer addresses the ECAC wide picture of the performance. For example, this can be the ECAC (Airport + TMA + En-route) fuel consumption, CO2 emission or delay.

En-route A defined area that is neither TMA nor airport.2 Note that in the Influence Model and Diagrams, this is displayed as “Enroute” rather than “En-route”.

Focus Area Within each KPA a number of more specific areas — Focus Areas — are identified in which there are potential intentions to establish performance management. Focus Areas are typically needed where performance issues have been identified. For example, within the Capacity KPA one can identify airport capacity, runway capacity and apron capacity as Focus Areas. Within the Safety KPA, the list of Focus Areas includes: accidents, incidents, mid-air collisions, CFIT accidents, runway incursions, safety management system maturity, etc.

KPA Key Performance Areas are a way of categorising performance subjects related to high level ambitions and expectations. ICAO has defined 11 KPAs: safety, security, environmental impact, cost effectiveness, capacity, flight efficiency, flexibility, predictability, access and equity, participation and collaboration, interoperability.

1 EATMP glossary 2 EP3 definition

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Term Definition

Local Performance Indicator The Local PIs layer for Airport, TMA and En-route represents a sub part of the Airport, TMA or En-route ECAC Performance Indicator to a local indicator. This addresses the local performance of an OI or a group of OIs. This can be the influence of group of OIs on the fuel consumption for a specific airport assessed by the validation exercise For example but then it will be needed to develop a methodology to extrapolate such result in order to obtain a value at ECAC level.

Metrics Supporting metrics are used to calculate the values of performance indicators. For example cost-per-flight-indicator = Sum(cost)/Sum(flights). Performance measurement is done through the collection of data for the supporting metrics (e.g. this leads to a requirement for cost data collection and flight data collection).

Performance Indicator (PI) Current/past performance, expected future performance (estimated as part of forecasting and performance modelling), as well as actual progress in achieving performance objectives is quantitatively expressed by means of indicators (sometimes called Key Performance Indicators, or KPIs). To be relevant, indicators need to correctly express the intention of the associated performance objective. Since indicators support objectives, they should not be defined without having a specific performance objective in mind.

Indicators are not often directly measured. They are calculated from supporting metrics according to clearly defined formulas, e.g. cost-per-flight-indicator = Sum (cost)/Sum(flights).

Performance measurement is therefore done through the collection of data for the supporting metrics.

Performance target (PT) Performance targets are closely associated with performance indicators: they represent the values of performance indicators that need to be reached or exceeded to consider a performance objective as being fully achieved.

SESAR The SESAR project (formerly known as SESAME) is the European air traffic control infrastructure modernisation programme. SESAR aims at developing the new generation air traffic management system capable of contributing to the safety and fluidity of air transport worldwide over the next 30 years.

TMA A control area normally established at the confluence of ATS routes in the vicinity of one or more major aerodromes.3 For consistency and convenience for performance aggregation of the measurement within the ECAC model there was a need to have a numerical representation. There is work ongoing in PRC to revise the current 30NM radius to probably 100NM as in US. Given that EP3 is considering a 100NM that will allow capturing most of the benefit in the TMA.

Uncertainty In statistics, an uncertainty is not a "mistake" but is a difference between a computed, estimated, or measured value and the true, specified, or theoretically correct value.

Table 1-1 Glossary of definitions

3 EATMP glossary

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1.5.2 Acronyms

Term Definition

ACC Area Control Centre

AIS Aeronautical Information System

ANS Air Navigation System

APU Auxiliary Power Unit

ASM Airspace Management

ATCO Air Traffic Controller

ATM Air Traffic Management

BDT Business Development Trajectory

BIC Best in Class

CDA Continuous Descendent Approach

CFIT Controlled Flight Into Terrain

CONOPS Concept of Operations

CNS Communication Navigation Surveillance

CSBT Coordinated Shared Business Trajectory

EC European Commission

ECAC European Civil Aviation Conference

E-OCVM European Operational Concept Validation Methodology

ER En-route

EP3 Episode 3

ERC EUROCONTROL

ESARR EUROCONTROL Safety Regulation Requirements

GHG Green House Gas emissions

GPM Global Performance Manual

HC Hydrocarbons

ICAO Internationale Civil Aviation Organisation

IFR Instrumental Flight Rules

IMC Instrumental Meteorological Conditions

ISBT Initial Shared Business Trajectory

KPA Key Performance Area

LoC Lines of Change

LTO Landing and Take-Off

MTOW Maximum Take Off Weight

OACI Organisation de l'Aviation Civile Internationale

OCE Operational Concept Element

OI Operational Improvement

PF Performance Framework

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Term Definition

PI Performance Indicator

PM Particulate Matter

PT Performance Target

QoS Quality of Service

RBT Reference Business Trajectory

ROT Runway Occupancy Time

SBT Shared Business Trajectory

SESAR Single European Sky ATM Research

SID Standard Instrument Departure

STAR Standard Terminal Arrival Route

STCA Short Term Conflict Alert

TMA Terminal and Manoeuvring Area

VFR Visual Flight Rules

VMC Visual Meteorological Conditions *

VOC Volatile Organic Compounds

Table 1-2 Glossary of Acronyms

1.6 DEFINITION OF THE EP3 INFLUENCE MODEL

The EP3 Influence Model (EP3 IM) was developed in a step-wise and iterative process. Initially a comprehensive set of independent influence diagrams was developed for each of the focus areas described in the Performance Framework Document [8]. These diagrams were based initially on the influence models that were developed for the SESAR D3 and D4 deliverables.

Following extensive consultation with EP3 partners, these diagrams were updated and then combined into one integrated influence diagram. During the final phase of this work, a selected number of the areas of the diagram were quantified. The objectives of this quantification were to:

• Show that the methodology of developing an influence model and using the results of validation exercises to populate the model is valid;

• Progress the quantification in as many areas of the model as possible given the time constraints.

The approach used to describe the impact of the concept for a number of the KPAs has been characterised using airspace organisation and management constructs. This has allowed the influence diagram study to build on existing work and thereby reduce timescales.

The Influence Model Study - Final Report [2], which describes the maturity of the model and the output results, describes how the level of expert judgement impacts upon the quality of the results and what steps need to be taken to improve the quality of the output.

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2 METHODOLOGY

2.1 INTRODUCING THE METHODOLOGY

Influence modelling is a very powerful technique to support complex decision making. It provides a clear graphical representation of a decision problem that is supported by a detailed mathematical model.

An influence model can be defined as a probabilistic network for reasoning about decision making under uncertainty. It is both a graphical and mathematical representation of a decision problem involving a sequence of interleaved decisions and observations.

The approach to this study is to develop an integrated, harmonised, coherent and validated influence model. This model will support the initial performance assessment of the SESAR Target Concept, focussing on the impact of IP1 and IP2 operational improvements.

The EP3 Influence Model is being developed in a step-wise, iterative, manner designed to ensure traceability to work originally conducted within the SESAR Definition Phase.

The following iterations of the model have been developed:

• Version 0 – SESAR D4 IDs in Analytica – this version of the model provided a transformation of existing SESAR D4 diagrams into the Analytica modelling environment. No attempt was made to verify validity of the content.

• Version 1 – Updated / New IDs for all KPAs – this version elaborated the V0 diagrams one step further by checking the content of specific variables, expanding and refining the content with elements of the SESAR D3 diagrams as well as with newly gathered information through the consultation process.

• Version 2 – Integrated IDs – this version integrated all individual Version 1 IDs into a single top-level diagram. The key objective of this version is to define commonalities, mutual dependencies and influences among the individual diagrams. No attempt of quantification has been made although the sources of data have been identified and the influence of OI-Steps has been proposed.

• Version 3 – Influence models (quantification of IDs) – this version transformed a number of the influence diagrams into influence models.

2.2 MODEL NOTATION

The modelling tool used for the influence diagrams is Analytica version 4.1. The notation used by Analytica is described in Table 2-1. It also describes where the EP3 IM study has amended the meaning of the variables in order to fit the scope and objectives of the study.

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Decision

Decision variable — a quantity that the decision maker can control directly.

The EP3 IM study uses the Decision variable to represent an Operation Improvement Step (OI Step).

Chance

Chance variable — an uncertain quantity whose definition contains a probability distribution.

Objective

Objective (utility) variable — a quantity that evaluates the relative value, desirability, or utility of possible outcomes. In an influence model, users are trying to find the decision(s) that maximize (or minimize) the value of this node.

The EP3 IM study uses the Objective variable to represent Key performance Indicators.

Variable

General variable — a quantity that is not one of the above classes. It can be uncertain because it depends on one or more chance variables. This variable shall be used in the initial development stage when the exact type of variable is unknown. Once the type of requirement becomes clearer, the type can be changed.

Module

Module — a collection of nodes organised as a diagram. Modules can themselves contain modules, creating a nested hierarchy.

The EP3 IM study uses modules to create a hierarchy of levels within the model. Modules are colour coded by KPA.

Index

Index variable — an index is used to define a dimension of an array.

Constant

Constant — a variable whose value is fixed. A constant is not dependent on other variables: it has no inputs.

Function

Function — either an existing function from a library can be used or a new function can be defined to augment the functions provided in Analytica.

The EP3 IM study uses the Function variable to represent an external simulation, dataset, tool or validation study that can be used to quantify the model.

Alias

Alias — a copy of a node, referring to the same variable, module, or other object as the original node. It is often useful to display an alias node in a different module than its original node. An alias node is identified by its title being shown in italics.

Table 2-1: Notation (as used in Analytica 4.1)

The above mentioned nodes are linked using arrows. There are several combinations and meanings of arrows, depending on the type of nodes they connect. The basic set of arrows is shown in Table 2-2 below.

Influence arrow – standard black arrow showing influence between two nodes.

Influence cycle (loop) – grey arrow used in dynamic function.

Variable 1 Variable 2

Arrow from variable node to variable node – indicates that target variable depends on the origin variable.

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Variable 1 Module

Arrow from variable node to module – indicates that at least one variable in the target module depends on the origin variable.

Variable 1Module

Arrow from module node to variable node – Indicates that the target variable depends on at least one variable in the origin module.

Module 1 Module 2

Arrow from module node to module node – indicates that the target module contains at least one variable that depends on at least one variable in the origin module.

Module 1 Module 2

Double-headed arrow between module nodes – indicates that each module contains at least one variable that depends on at least one variable in the other module.

Small arrowhead to the right or left of a variable node – indicates that the variable has a remote input or output — a variable that is not inside the displayed variable’s module.

Table 2-2: Influence arrows (as used in Analytica 4.1)

The approach taken when quantifying the model (see Final Report [2]) meant that not all of the detailed variables in the influence diagram were quantified. The influence model notation was amended to show which parts of the influence model are not quantified. An example of this is presented in Figure 2-1.

Dummy

Dummy

Dummy

Total enroutefuel burnt

Meteo Enroute

Additional distanceflown enroute per

flight

Fuel burnt enroutedue to additional

distance

Additional fuel burntenroute due to

vertical deviations

Direct route length

Extension due to enroute

design

Extension due to route

utilisation

Extension due to ATC

routing

Averageenroute fuel

burnt

Flight level capping

Numberflights(ECAC)

Average directfuel burn enroute

Averageadditional fuelburn enroute

Figure 2-1: Example influence model with variables not quantified on the left-hand side

Figure 2-1 shows that the variables on the left-hand side of the influence model that do not have a border to the nodes, and whose arrows do not quite reach the subsequent variables

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have not been quantified. In this example data is input directly into the following three variables:

• Average direct fuel burnt en-route4.

• Fuel burnt en-route due to additional distance.

• Additional fuel burnt en-route due to vertical deviations.

The data input for these three variables is then used in the influence model.

2.2.1 Model hierarchy

A single diagram / module containing more than 20 nodes can look too complicated. The structure of the model is organised into a hierarchy of modules. The objective of this layered approach is to make the diagrams clear and understandable, particularly for those who are not directly involved in the development process.

The top level influence diagram shows the Focus Areas of the KPAs, each as a separate module. Each of the Focus Areas contains the key influences as variables, or modules containing variables, and arrows indicating the dependencies among these.

2.2.2 Variable information – integrated documentation

Each variable in the EP3 IM has an object window, containing a set of attributes describing the variable. The object window shows the variable class, name, units of measurement, description and definition (mathematical relationship for calculation), list of inputs and outputs and optionally (where applicable) a reference to the source document on which the variable class, unit or definition is based.

There are advantages of using integrated documentation in Analytica when a variable is modified. Analytica automatically updates the list of inputs, outputs and arrows in the parent diagram to reflect any changes in the dependency relationships.

4 Note that in the Influence Model and Diagrams, “En-route” is abbreviated to “Enroute”.

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3 OVERVIEW OF THE INTEGRATED DIAGRAM The development of Version 3.0 of the influence diagram has captured six key performance areas and seventeen related focus areas integrated into one influence diagram. The top-level view of the integrated influence diagram is presented in Figure 3-1.

This top-level view of the influence diagram presents each of the KPAs and focus areas, which have been colour coded throughout the model to aid transparency of the model and navigation through the model.

KPAsFocus areas Common variables

Capacity

Network capacity

Airspace capacity

Airport capacityOI steps

Indexes

Model

Documentation

Predictability

On-time operation

Service disruption effect

Knock-on effect

Efficiency

Fuel-efficiency

Time-efficiency

Mission-effectiveness

Environment

Local Air Quality

Noise

Global Emissions

Flexibility

Service location flexibity

Sustainability for military requirements

BT update flexibility

Flexible access for non scheduled flights

SafetyATM-related safety outcome

Cost-effectivenessCost-effectiveness

Read input

data

Figure 3-1: Top-level view of the integrated influence diagram (Version 3.0)

The influence diagrams for each of the KPAs and focus areas are presented in Sections 4 to 10. The following section presents a description of the common variables that are used throughout the integrated influence diagram.

3.1 COMMON VARIABLES

One of the key objectives of the modelling of the influence diagrams for the EP3 Influence Model study is to ensure that the model is agile and flexible, transparent and that it allows the complete integration of the diagrams into a single environment.

To meet these objectives whilst minimising duplication of variables and to help ensure consistency throughout the model, it is necessary to define a number of variables that are used throughout the integrated diagram.

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The modules that encapsulate the common variables are listed on the top-level view of the influence diagram, which is presented in Figure 3-1. These include:

• OI Steps, which presents a complete list of Operational Improvement Steps;

• Indexes, which presents the list of indexes that are used throughout the diagram;

• Read Input Data module, which contains data read in from the input data spreadsheet.

A description of each of these modules, which contain the common variables, is presented in the following sections.

3.1.1 OI Steps

The ATM Process Model is a breakdown of the SESAR concept of operations (as presented in the SESAR 2.2.2 task deliverable). The model describes the SESAR ATM processes and presents the modelling decisions and assumptions that have driven the model breakdown.

The operational improvements that are encompassed by the SESAR concept of operations have been broken down into 183 OI Steps. These OI Steps are individual (but not necessarily independent) improvements to operations that may influence the performance of the ATM system in one or more KPA. Where there is a positive impact in one KPA, there may also be a negative impact in another.

The OI Steps are grouped within the OI Steps module into a number of groups, to aid navigation. They are categorised into the following groups:

• By Implementation Package (IP) number (i.e. IP1, IP2 and IP3), and then by grouping of OI Steps (i.e. AOM, DCB, CM etc.);

• By the related KPA (i.e. Efficiency, Capacity etc.).

They can also be found directly in the Analytica software by using the ‘Find’ function (press CTRL and F when in Analytica to reveal the ‘Find’ window, then type in the OI Step Code e.g. AOM0101), which will reveal the OI Step variable.

The influence of OI steps on each focus area has been identified. Within the model, the OI steps have been grouped into which implementation package they are encompassed, by drawing a grey box around them.

3.1.2 Indexes

The indexes module presents a list of the indexes that are used throughout the influence diagram. An index is used to define a dimension of an array. For example, instead of having one variable for each ACC in Europe one variable can be used and indexed by a list of the ACCs in Europe (the ACCs index). This enables one variable, when used with the ACC index, to capture information for each ACC in Europe. Note that the airspace structure in the future could contain FABs.

Further examples of indexes that are used include airports throughout Europe, IMC/VMC conditions and the identification of the Improvement Packages (IPs).

3.1.3 Read Input Data module

The Analytica model takes inputs directly from data contained in a MS Excel spreadsheet. This reduces the requirement to make changes to the data in the Analytica file. It is only possible to read in data from two dimensional tables. Therefore, since most of the variables in the model are multi dimensional, this module is used to read in 2-dimensional tables and combining them into single variables for use in the model.

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4 CAPACITY

4.1 AIRSPACE CAPACITY

The Airspace Capacity diagram illustrates the influences on the maximum number of flights that can be accommodated in a TMA or En-route sector. En-route and TMA airspace are treated separately but use the same basic structure.

Enroute

TMA

Enroute sectorDeclared hourly

capacity

TMA hourlycapacity

Enroute Structuralelements

Enroute Planning: Networkcapacity configuration

Enroute Situational factors

Enroute Tactical workload

TMA Structural elements

TMA Planning: Network

capacity configuration

TMA Situational Factors

TMA Tactical workload

Enroute equipagemix

Enroutepredictability buffer

Enroute conceptcapacity

TMA equipage mix

Enroute sectortransit time

TMA transit time

Variables set bypredictability

constraint

TMA conceptcapacity

TMA predictabilitybuffer

Variables set by

predictabilityconstraint

Figure 4-1: Airspace Capacity Influence Diagram

Both En-route and TMA capacity are affected by factors related to Planning, Situational factors, Airspace structure, Tactical workload and Equipage mix (for example percentage of self-separated flights and different avionics equipage). Equipage mix is not currently quantified or used in the calculations.

The airspace planning module influences the predictability buffer, which is applied to the concept capacity when scheduling traffic to allow for predictability of traffic flow – dependent on quality of planned demand information and quality of real time demand information

The predictability buffer is used as a constraint on a set of variables influenced by the Situational factors, Airspace structure, Tactical workload, together with an assumed transit time.

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These variables are then used to output the ‘concept capacity’ for a given sector or terminal area – the ‘concept capacity’ is the theoretical capacity before any buffers or constraints due to service delivery resources are taken into account.

Applying the predictability buffer to this concept capacity gives the declared hourly capacity.

This model has been quantified and example results are presented in Section 4.2.6.

4.2 EN-ROUTE CAPACITY

4.2.1 En-route Planning: Network capacity configuration

This module contains information on the configurability/ flexibility and quality of demand information. It is split into two sub modules.

Enroute Quality of planned

demand info

Enroute Configurability /

flexibility of capacity

Enroute Network capacityconfiguration

Figure 4-2: En-route network capacity configuration module

The value for the variable “Enroute Network capacity configuration” is expressed as a percentage representing the accuracy and the configurability of the sector. This percentage is then used as the predictability buffer.

4.2.1.1 En-route Quality of planned demand info

This module shows the influences on the quality of En-route planned demand information.

This represents the quality of planned information, which depends on the accuracy and completeness of traffic demand information, on the quality of demand synthesis, and on any OI steps impacting these variables.

IP2

Quality of Enrouteplanned demand

Information

AUO0203: Shared Business / MissionTrajectory (SBT)

AUO0204: Agreed Reference Business /Mission Trajectory (RBT) through

Collaborative Flight Planning

DCB0103: SWIM enabled NOP

Accuracy of EnroutePlanned Demand Info

Completeness of EnroutePlanned Demand Info

Quality of Enroute DemandSynthesis

ER Demand Volatility

IS0302: Use of Aircraft Derived Data

(ADD) to Enhance ATM Ground SystemPerformance

IS0303: Use of Predicted Trajectory (PT)to Enhance ATM Ground System

Performance

Figure 4-3: En-route quality of planned demand info

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4.2.1.2 Configurability / flexibility of En-route capacity

This module contains the configurability/flexibility of airspace capacity and shows the OI steps which influence this.

IP1

IP2

Configurability /flexibility of Enroute

capacity

DCB0208: Dynamic ATFCM using RBT

AOM0403: Pre-defined ATS Routes OnlyWhen and Where Required

AOM0801: Flexible SectorisationManagement

AOM0802: Modular Sectorisation

Adapted to Variations in Traffic Flows

AOM0402: Further Improvements to Route

Network and Airspace incl. Cross-Border

Sectorisation and Further Routeing Options

AOM0401: Multiple Route Options &

Airspace Organisation Scenarios

AUO0304: Initiating Optimal Trajectoriesthrough Cruise-Climb Techniques

CM0603: Precision Trajectory Clearances(PTC)-2D On User Preferred Trajectories

Figure 4-4: Configurability/flexibility of En-route capacity module

4.2.2 En-route Situational Factors

The En-route Situational Factors module, see Figure 4-5, contains three modules which influence the situational awareness of the controllers:

• En-route quality of real time demand info;

• En-route traffic complexity 3D;

• En-route traffic load smoothness/optimisation (time).

The result is a “percentage of interactions prevented” which is used to determine the number of interactions per sector hour and hence the controller workload.

Each module is elaborated in the sections below.

Situational Factors Enroute Quality of real time

demand information

Enroute Traffic complexity 3D

Enroute Traffic load smoothness/

optimisation (time)

Enroute situational factors -% interactions prevented

Figure 4-5: En-route: Situational Factors module

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4.2.2.1 En-route Quality of RT demand info

This module shows the variables which influence the quality of real time demand information – the accuracy of the 4D estimated trajectory, and the sophistication of the complexity management process.

IP2

IP1

Enroute Quality of(real-time) demand

information

Enroute Accuracy of 4Destimated trajectory

Enroute complexityassessment capability

CM0103: Automated Support forTraffic Complexity Assessment

CM0302: Ground basedAutomated Support for Managing

Traffic Complexity Across SeveralSectors

Figure 4-6: En-route quality of real time demand information module

4.2.2.2 En-route Traffic complexity (3D)

3-dimensional traffic complexity represents the workload of the controller due to the volume of flights within a sector, near its border, and on non-level segments within it.

This module contains information on the 3-dimensional traffic complexity En-route and shows the OI steps which influence this.

IP1

IP2Enroute Traffic complexity

(3D)

CM0302: Ground based Automated Support forManaging Traffic Complexity Across Several Sectors

AOM0402: Further Improvements to RouteNetwork and Airspace incl. Cross-Border

Sectorisation and Further Routeing Options

CM0301: Sector Team Operations Adapted to NewRoles for Tactical and Planning Controllers

CM0104: Automated Controller Support for

Trajectory Management

Figure 4-7: En-route traffic complexity (3D) module

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4.2.2.3 En-route Traffic load smoothness/ Optimisation (Time)

This module contains information on the workload of the controller due to the traffic load smoothness/optimisation in time and shows the OI steps which influence this.

IP1

IP2

Enroute Traffic loadsmoothness/optimisation (time)

AUO0203: Shared Business /

Mission Trajectory (SBT)

AUO0204: Agreed Reference Business/ Mission Trajectory (RBT) through

Collaborative Flight Planning

CM0102: Automated Support for

Dynamic Sectorisation and DynamicConstraint Management

CM0301: Sector Team Operations

Adapted to New Roles for Tactical andPlanning Controllers

TS0305: Arrival ManagementExtended to En Route Airspace

CM0101: Automated Support for

Traffic Load (Density) Management

CM0302: Ground based AutomatedSupport for Managing Traffic

Complexity Across Several Sectors

CM0403: Conflict Dilution by

Upstream Action on Speed

Figure 4-8: En-route traffic load smoothness/optimisation (time) module

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4.2.3 En-route Structural Elements

This module contains information on the route structure and flight levels of the sector along with the OI steps which have an influence on this information.

The result is a “percentage of interactions prevented” which is used to determine the number of interactions per sector hour and hence the controller workload.

IP1

IP2

Static route information

Flight levels

AOM0402: Further Improvements to Route Network and

Airspace incl. Cross-Border Sectorisation and Further Routeing

Options

AOM0401: Multiple Route Options & AirspaceOrganisation Scenarios

AOM0403: Pre-defined ATS Routes Only When andWhere Required

CM0603: Precision Trajectory Clearances (PTC)-2DOn User Preferred Trajectories

CM0701: Ad Hoc Delegation of Separation to FlightDeck - In Trail Procedure (ASEP-ITP)

Enroute Structural elements- % interactions prevented

Figure 4-9: En-route Structural Elements module

4.2.4 En-route Tactical workload

The En-route Tactical workload module (see Figure 4-10) contains three modules which influence the controllers’ tactical workload:

• En-route decision making: number and duration of clearances;

• En-route situational awareness and monitoring;

• En-route execution: communication and execution.

The results are the “Enroute decision making workload”, the “Enroute Execution Workload” (both expressed as a number of minutes per interaction) and the “Enroute Monitoring Workload” (expressed as a number of minutes per flight hour).

Each is elaborated in the sections below.

Tactical tasks

Enroute Decision making:

number & duration of clearances

Enroute Execution:

Communication and execution

Enroute Situational awareness &monitoring

Enroute Decision MakingWorkload

Enroute MonitoringWorkload

Enroute ExecutionWorkload

Figure 4-10: En-route tactical workload

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4.2.4.1 En-route Decision making: number & duration of clearances

This module contains information on the workload of the controller due to the number and duration of clearances and shows the OI steps which influence this.

IP1

IP2Decision making: number and

duration of clearances

CM0202: Automated Assistance to ATC Planning for

Preventing Conflicts in En Route Airspace

IS0303: Use of Predicted Trajectory (PT) to Enhance

ATM Ground System Performance

CM0201: Automated Assistance to Controller for

Seamless Coordination, Transfer and Dialogue

AUO0301: Voice Controller-Pilot Communications(En Route) Complemented by Data Link

AUO0302: Successive Authorisation of Reference

Business / Mission Trajectory (RBT) Segments using

Datalink

AUO0303: Revision of Reference Business / Mission

Trajectory (RBT) using Datalink

CM0301: Sector Team Operations Adapted to NewRoles for Tactical and Planning Controllers

CM0401: Use of Shared 4D Trajectory as a Means to

Detect and Reduce Potential Conflicts Number

CM0403: Conflict Dilution by Upstream Action on

Speed

CM0404: Enhanced Tactical Conflict

Detection/Resolution and Conformance & Intent

Monitoring

IS0302: Use of Aircraft Derived Data (ADD) to

Enhance ATM Ground System Performance

Figure 4-11: En-route decision making module

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4.2.4.2 En-route Situational awareness & monitoring

This module contains information on the workload of the controller due to situational awareness and monitoring and shows the OI steps which influence this.

IP1

IP2

Enroute Monitoring: situationalawareness & monitoring

AUO0503: In-trail Procedure inOceanic Airspace (ATSA-ITP)

CM0202: Automated Assistance toATC Planning for Preventing

Conflicts in En Route Airspace

CM0204: Automated Support forNear Term Conflict Detection &

Resolution and TrajectoryConformance Monitoring

CM0203: Automated FlightConformance Monitoring

Figure 4-12: En-route situational awareness and monitoring module

4.2.4.3 En-route Execution: Communication and execution

This module contains information on the workload of the controller due to communication and execution and shows the OI steps which influence this.

IP1

IP2 Enroute Execution:communication & coordination

CM0404: Enhanced Tactical ConflictDetection/Resolution and Conformance

& Intent Monitoring

AOM0102: Three Categories ofAirspace

CM0202: Automated Assistance toATC Planning for Preventing Conflicts

in En Route Airspace

CM0301: Sector Team OperationsAdapted to New Roles for Tactical and

Planning Controllers

CM0402: Coordination-free Transfer of Control through use of Shared

Trajectory

AUO0302: Successive Authorisation of Reference Business / Mission Trajectory

(RBT) Segments using Datalink

AUO0303: Revision of ReferenceBusiness / Mission Trajectory (RBT)

using Datalink

CM0201: Automated Assistance toController for Seamless Coordination,

Transfer and Dialogue

AUO0301: Voice Controller-PilotCommunications (En Route)

Complemented by Data Link

Figure 4-13: En-route execution module

Episode 3


Version : 2.01

- Page 31 of 143 -


4.2.5 Variables set by predictability constraint

This module contains variables that are set by the constraint of the predictability buffer and influenced by the Situational factors, Airspace structure, Tactical workload, together with an assumed transit time.

Flight interactions persector hour

Routine workload perinteraction

Monitoring workload perflight hour

Figure 4-14: Variable

episode 3 - eurocontrol.int · episode 3 d2.4.1-04a - influence diagrams update - annex to ep3...

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