Planning for Delay: influence of flight scheduling on airline punctuality
EUROCONTROL Trends in Air Traffic Volume 7
EUROCONTROL Acknowledgements
The idea for this study came from the Performance Review Commission reporting on the performance of European Air Navigation Services (ANS) in 2008 in the Performance Review Report (PRR20081).
The PRR2008 reports on Key Performance Areas of Safety, Punctuality and Predictability, Capacity/delays, Flight-Efficiency, Cost- Effectiveness and Environmental impact. Within the area of punctuality and predictability, a comparison between the USA and Europe showed similar arrival punctuality rates albeit with higher variability in the US. In section 7.4.4 of PRR2008 we read that “The gap between departure and arrival punctuality is significant in the US and quasi nil in Europe”. This document has been developed to help explain why this gap is so small in Europe and how airlines themselves can influence it.
Bo Redeborn, EUROCONTROL Director Cooperative Network Design, approved the further development of this series of studies with the objective of increasing the depth of knowledge. I am grateful to him for his support and encouragement.
Thanks go to the STATFOR team, Claire Leleu and Magda Gregorova for their technical support and expertise. I am grateful to EUROCONTROL’s Corporate Communications Service, Caroline Cochaux and Lucia Pasquini for their help in the design and publication of this document.
Thanks go to a number of people who gave their input, reviewed the document, suggested changes and helped in the proof reading. Notable amongst these were Milena Studic during her traineeship at CODA, Eric Moyson from IACA, Mark Deacon from Monarch Airlines, Daniella Massart from Brussels Airlines, Gerrit Klempert and Jens Armenat from Lufthansa. Any remaining errors are our own.
The views expressed in this document are those of the author and should not be construed to represent any official policy or view of the EUROCONTROL organisation itself.
Yves De Wandeler
Volume Author: EUROCONTROL Trends in Air Traffic
CODA Analyst
EUROCONTROL
1 www.eurocontrol.int/prc/gallery/content/public/PRR_2008.pdf
ii Planning for Delay: influence of flight scheduling on airline punctuality Trends in Air Traffic l Volume 7 Foreword
EUROCONTROL has a unique archive of detailed airline punctuality data in Europe, covering some 6 million flights per year (or 60% of all yearly filed flight plans). For more than ten years the Central Office for Delay Analysis (CODA) has been collecting scheduled and actual times direct from airlines.
Drawing on the trends it finds in the Agency archives, the Trends in Air Traffic series aims at giving an insight into some specific aspects of European aviation. The aim of these reports is to help stakeholders, and ourselves, to understand better the traffic trends that we see.
Increasingly, we are also making traffic and punctuality statistics available on the web through the CODA portal1 and STATFOR interactive dashboard2, but that has not taken away the value in having reference documents presenting the key figures.
Trends 23 discussed how flight delays are categorised and measured in Europe. This issue of Trends aims to bridge new planning indicators with post-flight delay analysis. The object of these studies is to inform and educate stakeholders across the industry thereby ensuring common understanding of the issue we face. We believe this report will be a useful contribution to the unders- tanding of this important characteristic of the Air Traffic Management network; a small contribution to improving performance of the network to everyone’s benefit.
David Marsh
Series Editor: EUROCONTROL Trends in Air Traffic
Head of Unit, Forecasting and Traffic Analysis
EUROCONTROL
1 See www.eurocontrol.int/coda. 2 See www.eurocontrol.int/statfor/sid. 3 A Matter of Time : Air Traffic Delays in Europe, EUROCONTROL Trends in Air Traffic Volume 2, September 2007.
Planning for Delay: influence of flight scheduling on airline punctuality Trends in Air Traffic l Volume 7 iii
Summary
Summary Trends in Air Traffic Volume 7 (TIAT7) – Planning for Delay
Building on TIAT2 (A Matter of Time: Air Traffic Delays in Europe) TIAT7 intends to elaborate further on the punctuality drivers for air traffic in Europe.
A key aspect of delay analysis is a good understanding of the definition of delay: “The time lapse which occurs when a planned event does not happen at the planned time.”
A crucial driver for good punctuality is good planning. An important source of information is the internal database of the airline. This can be enriched with external data if the airline’s own data source proves to be insufficient. The scheduling department of an airline has a very difficult task to create a “realistic” route programme for each (IATA) season that makes optimum use of the available resources.
When a schedule or block time is too long an airline will not be able to make optimum use of its resources (staff, airframe, infrastructure, etc). These resources will be blocked for too long and potential revenue is lost. On the other hand, an airline will generate a lot of rotational delays (Late Incoming Aircraft, Crew or Passengers from a previous Flight) if the schedule is too short. Flights leaving on time will in many cases arrive after the scheduled time of arrival and will potentially generate reactionary delays.
A scheduled block time (or timetable) can be influenced by numerous variables: distance that needs to be covered (or the city- pair), choice of airframe, availability of ATS routes (difference between weekdays and weekends), night curfews, availability of airport slots in the case of coordinated airports, inclusion of schedule padding, prevailing winds whilst in flight, taxi-times, etc.
In this issue of Trends in Air Traffic we take a closer look at the variability in the duration of the three phases of each flight between leaving the gate at the departure airport and arriving at the gate at the destination airport: Taxi-Out, Flight phase and Taxi-In. These three phases make the actual block time. Most airlines base their schedules on the length of historical block times. Any change in actual block times will ultimately have an effect on the scheduled times.
The Block Time Overshoot and Delay Difference Indicator-Flight are two new punctuality indicators that are introduced in this document. They are defined below.
The Block Time Overshoot (BTO) indicates the percentage of actual block times which are longer than the scheduled block time (during an observed period). The BTO of flights operated in Europe is typically between 25% and 35%.
The Delay Difference Indicator – Flight (DDI-F) is the difference between the arrival punctuality and departure punctuality expressed in minutes. Flights operated ahead of schedule can therefore have a negative delay figure. The DDI-F of flights operated in Europe, with a tendency to be slightly negative, is typically around -3 minutes.
In the current highly competitive market, airlines are constantly trying to reduce their cost base. One major cost element is fuel. Flying slower often means less fuel consumption and less costs. Will this have an effect on the future schedules?
Another important driver for good punctuality is a good understanding of events that may influence the airlines’ on-time perfor- mance and the implementation of a remedy in the case of serious operational shortcomings. A thorough post-flight analysis is essential in this regard. Cultivating a no-blame culture and correct data collection is paramount.
Data sharing helps to better understand the constraints of individual airlines. This is one of the strong aspects of the EUROCONTROL Central Office for Delay Analysis (CODA). By supplying data to CODA, airlines can access a database representing around 65% of all IFR flights in Europe1.
vi Planning for Delay: influence of flight scheduling on airline punctuality Trends in Air Traffic l Volume 7 The CODA data partners are aircraft operators, ANSP’s2, airports and CFMU3. Delay analysis based on CFMU data is referred to as ATFCM4 delays. Delay analysis based on data supplied by other data partners is referred to as “All Causes of delay”.
CODA publishes regular reports on the delay situation in Europe. Apart from these public reports, data partners can access on-line analysis tools via the secured pages of the CODA web portal. In this document, we take a closer look at the available tools and data sources on these secured web pages. More detailed information can also be found on www.eurocontrol.int/coda
This document is not a magic wand that can achieve a 100% punctuality rate for all flights, nor does it want to point at airlines performing below the European average. It is a guideline for all stakeholders to improve the understanding of delay analysis: comparing a schedule with the actual event.
New delay indicators and availability of data (through CODA) supplied by an increasing number of aircraft operators will enhance the analysis and understanding of delay occurrence and propagation.
And finally, this document also serves as a reference document by including tables of actual taxi-times at all major European airports in the annexes.
1 Europe: for the purpose of this study Europe consists of the EUROCONTROL Member States, see the Glossary for an overview of States included. 2 ANSP: Air Navigation Service Provider 3 CFMU: Central Flow Management Unit 4 ATFCM: Air Traffic Flow and Capacity Management
Planning for Delay: influence of flight scheduling on airline punctuality Trends in Air Traffic l Volume 7 vii viii Planning for Delay: influence of flight scheduling on airline punctuality Trends in Air Traffic l Volume 7 Contents
1. Introduction 1 2. CODA Statistics 4 3. Some definitions 7 4. The art of good scheduling 10 5. New CODA indicators for schedule sensitivity to arrival delays 17 5.1 Planner’s Indicator 1: Block Time Overshoot (BTO) 18 5.2 Planner’s Indicator 2: Delay Difference Indicator-Flight (DDI-F) 22 5.3 Example: Indicators for flights on Frankfurt to Istanbul route 25 6. vARIABLES influencing a flight schedule 30 6.1 Airport Pair by Level of Airport Slot Coordination 31 6.2 Airport opening hours 39 6.3 Operational aspects - Flight Time Limitations (FTL) 41 6.4 Taxi-times 43 6.5 Operating speed 47 6.6 Wind 50 6.7 Time of Operation 53 7. Leaving on-time or arriving on-time? 55 8. Delay Monitoring Systems & Use of CODA on-line applications 58 A. CODA data partners 67 B. Data items collected by CODA 70 C. IATA Delay codes list 71 D. CODA Delaygroups based on IATA Delay codes 76 E. 2009 Analysis of Taxi-Out Times at Airport of Departure 77 F. 2009 Analysis of Taxi-In Times at Airport of Destination 88 G. 2009 Taxi-Out Times by Wake Turbulance Category . 99 Glossary 102
Planning for Delay: influence of flight scheduling on airline punctuality Trends in Air Traffic l Volume 7 ix List of Figures
Figure 1 2009 distribution of IFR flights by ‘market segment’. 1
Figure 2 Monthly growth of largest market segments. 2
Figure 3 CODA coverage of Commercial Passenger flights in Europe. 4
Figure 4 Estimated cost of departure delays in Europe for delays longer than 15 minutes on commercial passenger flights. 5
Figure 5 Ratio of reactionary to primary delays based on total reported delay minutes on departure. 6
Figure 6 Primary Delay Distribution for 2008 based on total reported delay minutes. 6
Figure 7 Three phases of flight. 7
Figure 8 Distribution of Departure Delays All Causes by length of Delay. 11
Figure 9 Distribution of Arrival Delays All Causes by length of Delay. 14
Figure 10 yearly Average Departure and Arrival Delay per Movement “All Causes”. Flights departing or arriving ahead of schedule are counted as on-time. 15
Figure 11 Monthly Average Departure and Arrival Delay per Movement “All Causes”. Flights departing or arriving ahead of schedule are counted as on-time. 15
Figure 12 Monthly Average Departure and Arrival Delay per Movement “All Causes”. Flights departing or arriving ahead of schedule are counted as on-time. (Table indicating percentage difference between ADMA and ADMD) 16
Figure 13 yearly evolution of the Percentage of Delayed Flights (>15mins after Scheduled Time of Arrival/Departure) and the ratio of Reactionary to Primary delays during period 2003-2008. 19
Figure 14 yearly evolution of the BTO of the European Air Transport Network. 19
Figure 15 2007/2008 Monthly BTO for market segments LCC, Traditional Scheduled and Charter combined. 20
Figure 16 2007/2008 Monthly BTO by market segment -LCC. 21
Figure 17 2007/2008 Monthly BTO by market segment –Traditional Scheduled. 21
Figure 18 2007/2008 Monthly BTO by market segment –Charter. 21
Figure 19 2008 BTO and DDI-F by airport-pair (with at least 1000 observations). Each ‘X’ represents an airport-pair. 22
x Planning for Delay: influence of flight scheduling on airline punctuality Trends in Air Traffic l Volume 7 Figure 20 2007/2008 Monthly DDI-F. 23
Figure 21 2007/2008 Monthly BTO & DDI-F. 24
Figure 22 2007/2008 Monthly BTO & DDI-F by market segment –LCC. 24
Figure 23 2007/2008 Monthly BTO & DDI-F by market segment –Traditional Scheduled. 24
Figure 24 2007/2008 Monthly BTO & DDI-F by market segment – Charter. 24
Figure 25 Scheduled Block time evolution on flights from Frankfurt to Istanbul-Ataturk during 2007/2008. (A319/320/321 & B738’s) 26
Figure 26 Influence of Scheduled Block time on Arrival Punctuality on flights from Frankfurt to Istanbul-Ataturk. (A319/320/321 & B738’s) 27
Figure 27 Influence of Scheduled Block time on DDI-F on flights from Frankfurt to Istanbul- Ataturk. (A319/320/321 & B738’s) (Box represents 25th percentile low, 75th high and whisker represents 5th percentile low and 95th high) 27
Figure 28 Airport Class by Total IFR Departures in 2008. 32
Figure 29 Total IFR Departures in 2008 by Airport Class. 32
Figure 30 2008 European airports by Level of Coordination based on IATA WSG16th edition. 33
Figure 31 2008 Total European departures by airport Level of Coordination based on IATA WSG16th edition for market segments LCC, Traditional Scheduled and Charter. 33
Figure 32 2008 Proportion of IFR flights linking Coordinated, Schedules Facilitated and Non-Coordinated airports. 34
Figure 33 2008: BTO & DDI-F on City-pairs by Level of Coordination. 35
Figure 34 Monthly BTO of flights operated between Coordinated and Coordinated airports. 36
Figure 35 Monthly DDI-F of flights operated between Coordinated and Coordinated airports. 36
Figure 36 Monthly BTO of flights operated between Schedules Facilitated and Schedules Facilitated airports. 37
Figure 37 Monthly DDI-F of flights operated between Schedules Facilitated and Schedules Facilitated airports. 37
Figure 38 Monthly BTO of flights operated between Non-Coordinated and Non-Coordinated airports. 38
Figure 39 Monthly DDI-F of flights operated between Non-Coordinated and Non-Coordinated airports. 38
Figure 40 Düsseldorf Airport (EDDL). Distribution of flights on July 04, 2008 based on IOBT. 39
Planning for Delay: influence of flight scheduling on airline punctuality Trends in Air Traffic l Volume 7 xi Figure 41 Percentage of total daily delays caused by “Restrictions at Airport of Departure” (IATA delay code 89) at Düsseldorf Airport (EDDL) by 30 minute intervals starting at 03:30. The size of the bubble indicates the sum of the delay minutes. 40
Figure 42 Planned departures at London-City (EGLC) airport on 30 June 2008. First departures scheduled at opening of airport, last departure scheduled one hour before night ban. 40
Figure 43 Planned departures by hour as a percentage of daily departures. Departures on Saturday from the United Kingdom during summer 2008. 41
Figure 44 Hourly Average ATFCM Delay per Movement on Departure and Percentage of Flights Delayed by ATFCM Regulations on flights departing the United Kingdom on Saturday during summer 2008. 42
Figure 45 variations of taxi-out times (TXO) at some European airports (+KJFK) during summer 2008. 44
Figure 46 variations of taxi-in times (TXI) at some European airports (+KJFK) during summer 2008. 44
Figure 47 2008 Length of Flight time on flights from London-Heathrow to Paris-CDG. 45
Figure 48 2008 Length of Taxi-Times on flights from London-Heathrow to Paris-CDG. 45
Figure 49 2008: Hourly variations in average Taxi-Out times at some major European airports during summer 2008. 46
Figure 50 Ten-year price evolution Brent Crude Oil (in EUR). 48
Figure 51 Average speed of flights operated by carrier XYZ. (Network wide) 49
Figure 52 Average flight time and distance flown on city pair A-B by carrier XYZ. 49
Figure 53 Polar and subtropical jetstreams. 50
Figure 54 & 55 Flight times and Scheduled times influenced by prevailing winds aloft on Transatlantic Flights. 51
Figure 56 & 57 Monthly BTO and DDI-F on Transatlantic Flights. 52
Figure 58 & 59 Flight times and Scheduled times influenced by prevailing winds aloft. 52
Figure 60 & 61 Monthly BTO and DDI-F on flights to/ from SE Asia. 52
Figure 62 Overview of daily traffic share and Average Delay per Movement on Departure “All Causes” at leisure destination Kerkira/Corfu (LGKR) during June to August 2008. Non-coordinated during winter, coordinated during summer. 53
Figure 63 Overview of daily traffic share and Average ATFCM Delay per Movement on flights departing Hurghada (HEGN) in 2008. 54
Figure 64 Percentage of Delayed Flights on Departure > 15 mins of STD compared with Percentage of Delayed Flights on Arrival > 15 mins of STA. 56
xii Planning for Delay: influence of flight scheduling on airline punctuality Trends in Air Traffic l Volume 7 Figure 65 Average Delay per Movement on Departure compared with Average Delay per Movement on Arrival. 56
Figure 66 Average Delay per Delayed Departure > 15 mins and Average Delay per Delayed Arrival > 15 mins. 57
Figure 67 Primary departure delay causes 2008 vs. 2007. 60
Figure 68 CODA – Airline application. Access to CORE and Analysis Tool. 62
Figure 69 Front page CORE. (CODA Report) 62
Figure 70 Screenshot CODA On-Line Analysis Tool. 63
Figure 71 Screenshot CODA On-Line Analysis Tool – General Statistics – map tool. 64
Figure 72 Screenshot CODA On-Line Analysis Tool – Significant Events. 64
Figure 73 Screenshot CODA On-Line Analysis Tool – Airport Map tool. 65
Planning for Delay: influence of flight scheduling on airline punctuality Trends in Air Traffic l Volume 7 xiii xiv Planning for Delay: influence of flight scheduling on airline punctuality Trends in Air Traffic l Volume 7 1. INTRODUCTION
Delays occur “when a planned event does not happen at the planned time”1. Though the schedule is planned months before the flight, there are rich sources of quantitative data on daily operations that, depending on the business model used, can assist an aircraft operator to plan more effectively.
The word ‘‘planned’’ occurs twice in the definition of delay, and yet the focus of actions to reduce delay often falls on the tactical operations - at airlines, airports and in air traffic management Additional– rather than Flight/Day on the planning of schedules. Perhaps this is partly because operations are an activity rich in data and performance1500 indicators, with actions that translate rapidly into measurable changes in performance. 1000
Schedule planning, meanwhile, is much further removed 500from the action; by the time the performance of the airline’s Summer timetable becomes clear, the planner is already putting the finishing touches to the Winter timetable. As a result, in many airlines planning is more an art than a science. 0 -500 Nevertheless, one of the cornerstones for achieving the best possible on-time performance is the creation of a realistic schedule. -1000 Business Aviation This document aims to redress the balance. We aim to show that moreTraditional can Scheduled be done at the planning stage to manage on-time performance, and that there is a large amount of data that is availableAll-Cargo to help planners. From the perspective of planning, the -1500 report will look at some key aspects of the definition and analysis of flightNon-Scheduled delays including: Low-Cost Non-Scheduled -2000 Military The creation of a schedule (see section 4) -2500 Monitoring of actual times (see section 5) Guidance in block time setting (see section 6) Jul-05 Jul-06 Jul-07 Jul-08 Jul-09 Jul-10 Jan-05 Jan-06 Jan-07 Jan-08 Jan-09 Jan-10 Data and knowledge sharing (see section 7) Oct-10 Punctuality analysis tools: CODA on-line applications (see section 8)
The optimum rate of on-time performance will vary by aircraft operator but will always take the level of customer satisfaction and consequent financial cost into account. There are limits: any airline trying to achieve 100% on-time performance will find the financial cost to achieve this goal too high. At the other end of the scale, a lack of applied resources will result in poor on-time performance which means unsatisfied customers and ultimately loss of revenue.
There is no single right answer; aircraft operators use diffe- rent business models or operate different types of flights. 5.88% Some operators work to a rigid schedule that is fixed 3.17% 58.44% months in advance, others determine a schedule only hours 6.89% before a flight departs. The EUROCONTROL Statistics and 3.32% Forecast Service STATFOR2 publishes statistics by market segment: traditional scheduled, low-cost carriers (LCC), charter, business aviation, cargo, military and others. The All IFR distribution of IFR flights by market segment for 2009 in Trac 2009 Charter Europe are shown in Figure 1. All-Cargo Business Aviation Other Low-Cost Military 20.49% Traditional Scheduled 1.80%
Figure 1 - 2009 distribution of IFR flights by market segment.
1 A Matter of Time: Air Traffic Delay in Europe, EUROCONTROL Trends in Air Traffic, Volume 2, September 2007. 2 www.eurocontrol.int/statfor
Planning for Delay: influence of flight scheduling on airline punctuality Trends in Air Traffic l Volume 7 1 This document will concentrate on three of these segments which together account for approximately 85% of IFR1 flights in Europe:
n Traditional Scheduled flights, e.g. ‘flag carriers’ and regional airlines; n Charter flights (including leisure, charter and non-scheduled flights); n Low cost flights (e.g. LCC’s).
The market segments not addressed are business aviation, all cargo, military flights, other flights (i.e. test and training flights), helicopter flights (e.g. flights to oil rigs), state flights, fire and rescue flights, etc. Some of these may follow something that resembles a schedule and therefore operators may still find analysis here that is useful for their planning.
Due to the significant drop in traffic for all market segments in 2009 (compared to previous years) the analysis in this document was based on 2008 data unless otherwise specified. See Figure 2 for an overview of the growth (and negative growth) of traffic over recent years.
Additional Flight/Day 1500
1000
500
0
-500
-1000 Business Aviation Traditional Scheduled All-Cargo -1500 Non-Scheduled Low-Cost Non-Scheduled -2000 Military -2500 Jul-05 Jul-06 Jul-07 Jul-08 Jul-09 Jul-10 Jan-05 Jan-06 Jan-07 Jan-08 Jan-09 Jan-10 Oct-10
Figure 2 - Monthly growth of largest market segments.
1 Instrument Flight Rules 5.88% 3.17% 58.44% 6.89%
3.32% 2 Planning for Delay: influence of flight scheduling on airline punctuality Trends in Air Traffic l Volume 7
All IFR Trac 2009 Charter All-Cargo Business Aviation Other Low-Cost Military 20.49% Traditional Scheduled 1.80% Two distinct business models can be identified in the group of airlines that work with rigid schedules: airlines operating in a hub-and-spoke (traditional scheduled) and those focused on point-to-point flights (LCC & Charter).
The choice of business model has an impact on the flight scheduling:
Airlines operating a hub-and-spoke network will have to streamline arrival and departing flights in order to offer good connections for passengers flying through the hub (or home base). If the connecting time is too long passengers will opt for a direct flight (with a competitor). In the case when the connecting time is too short there is a high risk that a passenger will not be able to make the onward journey. In these cases additional re-routing or hotel costs will lower the profit margin on these flights.
Airlines operating a point-to-point network will not be able to offer the same frequency compared to airlines operating a hub-and- spoke network. The nuisance of lower frequency is offset by the shorter journey time.
The level of coordination at the airport of departure and the destination airport may have an influence on the final schedule. When the available airport slots are scarce, airlines will have a difficult task finding a good schedule by joining a limited amount of available airport slots at the airport of departure and the destination airport (see section 6.1.).
Planning for Delay: influence of flight scheduling on airline punctuality Trends in Air Traffic l Volume 7 3 2. CODA STATISTICS
The analysis in this report is based on CODA’s unique archives of delay and flight data for Europe. This voluntary reporting scheme collects operational data from CFMU, ANSP’s1, airlines and airports and makes it available to anybody with an interest in delay analysis. This database contains historical data on millions of flights starting from 2001.
EUROCONTROL’s Central Office for Delay Analysis (CODA) collects operational data from airlines operating IFR flights in Europe. In 2008, more than 120 airlines supplied flight-by-flight operational data on a voluntary basis covering around 65% of commercial passenger flights2 in Europe. In return these airline data partners were given access to a range of on-time performance reports, benchmarks and analysis tools. See Annex A for an overview of data suppliers and Annex B for a list of data items that are collected. More detailed information can be found at www.eurocontrol.int/coda. Figure 3 shows how CODA’s coverage of IFR flights has expanded in recent years.
70%
60%
50%
40%
30% Jun-05 Jun-06 Jun-07 Jun-08 Dec-05 Dec-06 Dec-07 Dec-08
Figure 3 - CODA coverage of Commercial Passenger flights in Europe.
Delay monitoring and analysis is an important aspect of the airlines’ operational and financial success. The cost of delay is estimated at €82 per minute of delay3 for delays in excess of 15 minutes. Looking at the CODA data and extrapolating the percentage of delayed flights (with a departure > 15 minutes after STD) to all flights in Europe the total cost of delays from all causes is estimated at more than € 7 billion in 2008. (see Figure 4)
1 ANSP: Air Navigation Service Provider 2 Commercial Passenger flights in this context groups traditional scheduled, charter and low cost flights. 3 See PRR2009, Performance Review Report, An Assessment of Air Traffic Management in Europe, during the Calendar Year 2009, 20 May 2010 (Chapter 9). A digital copy is available on www.eurocontrol.int/prc
4 Planning for Delay: influence of flight scheduling on airline punctuality Trends in Air Traffic l Volume 7 8000
7000
6000
5000
4000
(in million EUR) 3000
2000
1000 Cost of Departure Delays > 15 minutes of DepartureCost Delays
0 2004 2005 2006 2007 2008
Figure 4 - Estimated cost of departure delays in Europe for delays longer than 15 minutes on commercial passenger flights. Based on the percentage of delayed flights > 15 minutes after STD reported to CODA and projected to all flights operated in Europe. Cost of Delay: €82 per minute on average for delays longer than 15 minutes (2008 prices)
The data provided by airlines to CODA include a classification of each minute of delay by cause of delay. In Europe, reasons for flight delays are assigned on departure using the IATA list of delay codes1. Delay reasons can be split in two groups: Primary delays and Reactionary delays. Primary delays can be linked directly to a specific flight. Typical examples are ATFCM delays, handling related delays or delays caused by technical problems. Delays which are the direct result of earlier delays are referred to as reactionary delays. Examples are late incoming aircraft, awaiting crew or passengers from a previous flight.2
Looking at the ratio of reactionary to primary delays we notice a strong increase over recent years. In 2003, for each minute of primary delay there was 0.54 minutes of reactionary delay. The ratio increased to 0.83 in 2008 (see Figure 5).
Reactionary delays have an increasing influence on the financial and operational results of airlines in Europe. A future issue of Trends in Air Traffic will investigate reactionary delays further. This issue will be based on a study by the RWTH University of Aachen3 using CODA data and expertise.
1 Airline delay reports are translated into IATA delaycodes when the input of the reporting airline is using a customised list of delaycodes. See Annex C for the list of IATA delaycodes. 2 A Matter of Time : Air Traffic Delay in Europe, Eurocontrol Trends in Air Traffic Volume 2, September 2007 (Section3). 3 The propagation of air transport delays in Europe, thesis by Martina Jetzki for the Department of Airport and Air Transportation Research RWTH AACHEN UNIVER- SITY, 23 December 2009. A copy of the report can be downloaded from www.eurocontrol.int/coda
Planning for Delay: influence of flight scheduling on airline punctuality Trends in Air Traffic l Volume 7 5 0.85
0.80
0.75
0.70
0.65
0.60
0.55 Ration reactionaryRation / primary delays
0.50 2003 2004 2005 2006 2007 2008
Figure 5 - Ratio of reactionary to primary delays based on total reported delay minutes on departure.
The largest single group of delay reasons by total generated delay minutes are delays caused by airline operational processes. They account for approximately 50% of the primary delays. This group is followed by airport and en-route delays which account for almost one-third of all delays. Weather delays may vary by season. See Figure 6 for a full overview of the 2008 distribution of primary delays. An overview of IATA delay codes for each group is provided in Annex C.
10% 54% 3% 3% Airline Airport 13% En-Route Miscellaneous Security Weather Primary Delay distribution for 2008 Delay from 1 minute onwards categorised by IATA-Delay Codes as: Airlines: Codes 0 to 69,97 Airport: Codes 83,86 to 89 Weather: Codes 71 to 79,84 Security: Codes 85 En-Route: Codes 81,82 17% Misc: Codes 98,99
Figure 6 - Primary Delay Distribution for 2008 based on total reported delay minutes.
Unless otherwise stated CODA data was used for the graphs and analysis in this document.
6 Planning for Delay: influence of flight scheduling on airline punctuality Trends in Air Traffic l Volume 7 3. SOME DEFINITIONS
This section lists the main time markers during a flight and summarises the delay measurements that use these markers.
Airline scheduling departments and airport slot coordinators communicate in a language which is often referred to as “IATA- language”, i.e. using acronyms from IATA. Airline flight operations and Air Navigation Service Providers use ICAO language and acronyms. The IATA and ICAO acronyms often mean the same but, for delay analysis, there is one very important difference: references to time stamps within the IATA language are almost exclusively in local time and therefore subject to time zones and daylight-saving time (DST) whereas timestamps in ICAO-language are in coordinated universal time (UTC-time), which is not subject to time zones or daylight saving.
These days, airlines fine-tune their schedules throughout the year. However, for many airlines the schedules are largely fixed within each of two IATA ‘seasons’. The fact that daylight saving is important in scheduling is also reflected in the fact the IATA seasons change at the same time as Europe switches to and from daylight saving, even though other parts of the World intro- duce and end daylight saving at other times.
In recent years, the iata seasons have been:
W06 IATA winter season 2006 (from 29-10-2006 till 24-03-2007) S07 IATA summer season 2007 (from 25-03-2007 till 27-10-2007) W07 IATA winter season 2007 from 28-10-2007 till 29-03-2008) S08 IATA summer season 2008 (from 30-03-2008 till 25-10-2008) W08 IATA winter season 2008 (from 26-10-2008 till 28-03-2009)
There are three distinct flight phases:
Taxi-out (TXO): starts when the aircraft leaves the parking position (OUT) and ends with the Take-off (OFF) En-Route (ENR): starts with the Take-off (OFF) and ends with the landing (ON) Taxi-in (TXI): starts with the landing (ON) and ends when the aircraft reaches the parking position (IN)
Out Off On In
Taxi-Out En-Route Taxi-In
Figure 7 - Three phases of flight.
Planning for Delay: influence of flight scheduling on airline punctuality Trends in Air Traffic l Volume 7 7 The main time stamps in a flight schedule are:
STD Scheduled Time of Departure (from the gate) STA Scheduled Time of Arrival (at the gate) ATD Actual Time of Departure (from the gate) (ACARS1: OUT, also known as ‘off blocks’) TKOF Actual Take-Off Time (ACARS: OFF) LDG Actual Landing Time (ACARS: ON) ATA Actual Time of Arrival (at the gate) (ACARS: IN, also known as ‘on blocks’) TXO Taxi-Out Time, time between ATD and TKOF TXI Taxi-In Time, time between LDG and ATA Flight Time between TKOF and LDG
For these time stamps, the ‘scheduled time’ refers to the time in the published schedule, rather than, say, the time in the most recent flight plan.
Using these times, a number of useful measurements can be calculated:
Block time Time from departure from the gate to arrival at the next gate, either scheduled or actual
BTO Block Time Overshoot, the percentage of flights with an actual block time which exceeds the scheduled block time. (This is introduced and explained in section 5.1)
DDI-F Delay Difference Indicator – Flight, the punctuality at the end of the flight compared with the punctuality at the start of the phase expressed in minutes. (This is introduced in section 5.2)
ADMD Average Delay per Movement on Departure. Flights leaving ahead of schedule are considered delay neutral:
∑ (ATD-STD) ifATD>STD ADMD= ∑ (ATD-STD) ifATD>STD ADMD= Number of Departures Number of Departures ADMA Average Delay per Movement on Arrival. Flights arriving ahead of schedule are considered delay neutral: ∑ (ATA-STA) ifATD>STD ADMA= ∑ (ATA-STA) ifATD>STD ADMA= Number of Arrivals Number of Arrivals
1 ACARS: Aircraft Communications Addressing and Reporting System, digital datalink system for transmission of short messages between aircraft and ground stations via radio or satellite.
8 Planning for Delay: influence of flight scheduling on airline punctuality Trends in Air Traffic l Volume 7 PDF-D(15) Percentage of Delayed Flights on Departure is the share of total flights departing more than 15 minutes after the Scheduled Time of Departure. In this situation the threshold to determine if a flight is delayed is set at 15 minutes. Other thresholds may be used in other studies/reports (5, 15, 60 minutes etc)
PDF-A(15) Percentage of Delayed Flights on Arrival is the share of total flights arriving more than 15 minutes after the Scheduled Time of Arrival. In this situation the threshold to determine if a flight is delayed is set at 15 minutes. Other thresholds may be used in other studies/reports (5, 15, 60 minutes etc).
PAF-D(00) Percentage of Advanced Flights on Departure is the share of total flights leaving ahead of the Sche- duled Time of Departure. In this situation a flight is counted as ahead of schedule if the aircraft leaves one minute or more ahead of the scheduled time of departure. Other thresholds may be used in other studies/reports (5, 15, 60 minutes etc).
PAF-A(00) Percentage of Advanced Flights on Arrival is the share of total flights arriving ahead of the Scheduled Time of Arrival. In this situation a flight is counted as ahead of schedule if the aircraft arrives one minute or more ahead of the scheduled time of departure. Other thresholds may be used in other studies/ reports (5, 15, 60 minutes etc).
Planning for Delay: influence of flight scheduling on airline punctuality Trends in Air Traffic l Volume 7 9 4. THE ART OF GOOD SCHEDULING
Airline scheduling is often more an art than a science, although airlines will try their utmost to base their work on as much science as they possibly can. Airlines operations are influenced by a vast amount of predictable and unpre- dictable events. Some events can be forecast with a high rate of probability (e.g. number of days of fog, the wind direction and speed, etc.) whilst other events can be considered as “Acts of God” and almost impossible to take into account during the scheduling phase (e.g. volcanic eruptions, political unrest, etc.).
Choice of Schedule
In principle, airlines are free to draft their own timetable, i.e. the scheduled time of departure at the airport of departure and the scheduled time of arrival at the destination airport. In practice, this is a complex exercise in which airline planning and sche- duling departments have to balance the availability of resources (staff, facilities & equipment) with economic and marketing targets whilst meeting all safety and legal regulations and the availability of slots at airports (see section 6.1).
Flight schedules are often based on the observations of the actual block times during previous seasons (if such information is available). The scheduled times of competitors can be taken into account, but many operational variables - starting with aircraft types – may not be identical. The schedules of competitors will therefore usually only be used as a marketing bench- mark rather than an operational input.
Optimum Schedule
An optimum schedule is a schedule that best reflects the expected travel time between two airports and at the same time balances the needs of passengers, shippers and the aircraft operator. It is the sum of the three distinct phases of each flight: Taxi-Out phase, En-Route (or Flight) phase and Taxi-In phase.
An optimum schedule should not be too short, meaning that a flight that leaves on time is likely to arrive with a delay. Arrival delays will cause reactionary delays and may spread through the whole network (of the airline).
An optimum schedule should not be too long either, meaning that flights that leave on time will arrive ahead of schedule at the destination. Flights that arrive ahead of schedule might upset the planning at the destination airport, e.g. airport stand and gate allocation, ground staff planning etc. This will also result in an overestimation of airline resources (aircraft, staff, etc.) required to execute the scheduled programme.
Predictability in the Schedule
Predictability is essential information in building schedules: a high level of punctuality can be guaranteed to passengers if delays are predictable and incorporated in schedules. To maintain schedule integrity and deliver on-time performance to their customers, airlines include time-buffers which can be integrated in the ground phase or in the flight phase. Airlines can also opt for reserve aircraft and crew, but this lowers their resource utilisation and therefore profitability.
Improved predictability can lead to improved punctuality or significant savings through better use of human and physical resources.
As indicated by the PRC1 in the PRR20052 the potential savings are high. For example, the cost of one minute of strategic buffer for an A320 is estimated at €49. By cutting an average of five minutes off 50% of schedules, thanks to better predictability of operations during the scheduling phase, would be worth some €1000M per annum.
1 Performance Review Commission. 2 See PRR2005: Performance Review Report 2005, April 2006, § 4.5.5.
10 Planning for Delay: influence of flight scheduling on airline punctuality Trends in Air Traffic l Volume 7 Airlines may decide to include a buffer in the schedule in case of expected departure delays. This buffer will improve the arrival punctuality and reduce the impact of reactionary delays on the overall level of punctuality.
A schedule buffer (or schedule padding) mitigates the cost of departure delays. This results in a financial cost for the airline if no departure delay occurs (or when the flight left ahead of schedule) because resources were “blocked” for no reason. It will also mean that aircraft will spend longer on the ground than foreseen, and actual crew duty times will be lower than budgeted, etc.
The percentage of flights departing within 15 minutes3 of the Scheduled Time of Departure (STD) increased slightly from 76.5 % in 2007 to 77.2% in 2008. This minor improvement comes after four years of continuous deterioration from the 83.3% achieved in 2003.
The PAF-D(00) (Percentage of Advanced Flights on Departure, as from 1 minute ahead of schedule) was 28.1% in 2008 compared to 26.1% in 2007. This change is the first “real” change in PAF-D(00) data, which has been stable at around 26% since 2003. (see Figure 8).
30%
25%
20% 2007 2008
15%
10%
5%
0% PAF-D>60 PDF-D>60 PAF-D5-15 PAF-D31-60 PAF-D16-30 PAF-D00-04 PDF-D00-04 PDF-D05-15 PDF-D16-30 PDF-D31-60
Figure 8 - Distribution of Departure Delays All Causes by length of Delay.
3 From 15 minutes ahead of the STD to 15 minutes after STD.
Planning for Delay: influence of flight scheduling on airline punctuality Trends in Air Traffic l Volume 7 11
The percentage of flights arriving within 15 minutes of the Scheduled Time of Arrival (STA) on the other hand changed only a little, from 69.0% in 2007 to 68.8% in 2008. This small change masks an opposite shift: an increase of flights arriving more than 15 minutes before STA (+0.7%) which is offset by a decrease in flights arriving more than 15 minutes after STA (-0.6%) (see Figure 9).
Although passengers will generally appreciate the fact that more flights arrive (more than 15 minutes) ahead of schedule, this also brings more instability to the network (e.g. park and gate allocation at airports, staff planning for Ground Handling Agents, changed mix of departing and arriving traffic for ATC, etc). Additional analysis and study is necessary to determine the true impact of the increase in early arrivals.
30%
25%
20% 2007 2008
15%
10%
5%
0% PAF-A>60 PDF-A>60 PAF-A5-15 PAF-A31-60 PAF-A16-30 PAF-A00-04 PDF-A00-04 PDF-A05-15 PDF-A16-30 PDF-A31-60
Figure 9 - Distribution of Arrival Delays All Causes by length of Delay.
In 2007, 1.1% of flights departed more than 15 minutes ahead of STD and 8.7% arrived more than 15 minutes ahead of STA. Looking at the delays above 15 minutes, we note that 22.4% of flights departed more than 15 minutes after STD and 22.3% arrived more than 15 minutes after STA (see Figure 8 & Figure 9).
In 2008, 1.3% of flights departed more than 15 minutes ahead of STD and 9.5% arrived more than 15 minutes ahead of STA. Looking at the delays above 15 minutes, we note that 21.5% of flights departed more than 15 minutes after STD and 21.7% arrived more than 15 minutes after STA (see Figure 8 & Figure 9).
Almost 10% of all flights in 2008 arrived more than 15 minutes ahead of schedule, this was mostly caused by a shorter than planned actual block time instead of a departure which was more than 15 minutes ahead of schedule.
14 Planning for Delay: influence of flight scheduling on airline punctuality Trends in Air Traffic l Volume 7 In 2008, the ADMD1 “All Causes” was 12.5 minutes whereas the ADMA2 was 12.3 minutes. This means that the Average Delay per Movement decreased by 2% between the Off-Block and the On-Block of a flight. In 2007, the decrease was 3%, with an ADMD of 12.8 minutes and the ADMA 12.4 minutes (see Figure 10 for a yearly evolution of the ADMD and ADMD during recent years and Figure 11 for a monthly evolution in 2007/2008).
The (small) decrease in Average Delay per Movement between the departure and arrival phase indicates that airlines try to achieve a high level of predictability by including a time-buffer in the schedule, as well as working on the day of operations to make up for earlier delays.
14
13
ADMD 12 ADMA
11
10
Average Delay per Movement in Minutes per Movement Delay Average 9
8 2003 2004 2005 2006 2007 2008 Figure 10 - Yearly Average Departure andYear Arrival Delay per Movement “All Causes”. Flights departing or arriving ahead of schedule are counted as on-time.
ADMD ADMA 20 20
15 15
10 10
5 5
0 0 Jul-07 Jul-08 Oct-07 Oct-08 Jan-07 Jan-08 Jun-07 Jun-08 Apr-07 Apr-08 Feb-07 Feb-08 Dec-07 Dec-08 Sep-07 Sep-08 Nov-07 Nov-08 Mar-07 Mar-08 Aug-07 Aug-08 May-07 May-08 Figure 11 - Monthly Average Departure and Arrival Delay per Movement “All Causes”. Flights departing or arriving ahead of schedule are counted as on-time.
1 ADMD: Average Delay per Movement on Departure “All Causes” 2 ADMA: Average Delay per Movement on Arrivals “All Causes”
Planning for Delay: influence of flight scheduling on airline punctuality Trends in Air Traffic l Volume 7 15 Difference ADMA ADMD ADMA vs. ADMD Jan-07 12.54 12.90 3% Feb-07 10.66 10.75 1% Mar-07 11.02 11.07 0% Apr-07 10.23 9.92 -3% May-07 11.80 11.57 -2% Jun-07 16.17 15.94 -1% Jul-07 16.36 15.39 -6% Aug-07 13.03 12.03 -8% Sep-07 12.01 11.53 -4% Oct-07 12.47 12.06 -3% Nov-07 11.43 10.90 -5% Dec-07 15.38 15.19 -1% Jan-08 12.15 12.31 1% Feb-08 12.14 12.48 3% Mar-08 13.19 13.10 -1% Apr-08 10.87 11.04 2% May-08 11.42 11.32 -1% Jun-08 13.83 13.16 -5% Jul-08 14.63 13.71 -6% Aug-08 14.00 13.10 -6% Sep-08 12.27 11.99 -2% Oct-08 10.39 10.30 -1% Nov-08 11.22 11.36 1% Dec-08 14.17 14.21 0%
Figure 12 - Monthly Average Departure and Arrival Delay per Movement “All Causes”. Flights departing or arriving ahead of schedule are counted as on-time. (Table indicating percentage difference between ADMA and ADMD)
16 Planning for Delay: influence of flight scheduling on airline punctuality Trends in Air Traffic l Volume 7 5. NEW CODA INDICATORS FOR SCHEDULE SENSITIVITY TO ARRIVAL DELAYS
An optimal schedule should be delay neutral: a schedule that is not too short - meaning that a flight that left on-time arrives with a delay. Nor should it be too long meaning flights that depart on-time arrive ahead of the schedule. To help turn this idea into practice, two new indicators have been introduced to help airline schedulers determine the optimal schedule based on historical flight data: the “Block Time Overshoot” and “Delay Difference Indicator - Flight”.
Arrival punctuality is mainly influenced by departure punctuality. An optimal schedule should be delay neutral; it should not add delay during the flight phase, neither should it serve as a buffer because this is not cost effective. In practice, even an excellent schedule will see delays, but these should not be delays related to scheduling, i.e. these delays are not embedded in the schedule (see Section 4. The art of good scheduling). A challenge for the planner is to know how to use data on past performance of the schedule and identify when changes should be made, without getting bogged down in the details of performance on individual days. A planner should not plan in a vacuum, but share and use all available data.
To help turn the idea that a schedule should be delay neutral into practice, two new indicators have been introduced to help airline schedulers determine the optimal schedule based on historical flight data: the “Block Time Overshoot” and “Delay Difference Indicator - Flight”. These indicators do not analyse the details of departure or arrival punctuality as such. They aim to give more information on a schedule’s sensitivity to arrival delays at an aggregate level. That is, they allow the planner to ask whether, with a given departure delay the schedule is delay neutral, or serves to recover from departure delays, or adds delay to a flight.
Looking at all IFR flights operated in Europe we observe that 30%1 of operated fights have a block time exceeding the scheduled block time. Despite this, airlines were able to reduce the arrival delay by 3 minutes compared to the departure delay.
Based on these observations, two new indicators are introduced:
Block Time Overshoot (BTO), which is the percentage of flights with an actual block time exceeding the scheduled block time (see section 5.1)
Delay Difference Indicator – Flight (DDI-F) which is the difference between the arrival and departure punctuality expressed in minutes (see section 5.2)
1 Based on 2008 CODA data.
Planning for Delay: influence of flight scheduling on airline punctuality Trends in Air Traffic l Volume 7 17 5.1 Planner’s Indicator 1: Block Time Overshoot (BTO)
“Block Time Overshoot” is the percentage of flights with an actual block time exceeding the scheduled block time. Analysis of European delay data suggests a planner should aim at keeping this indicator around 30-35%.
The first of the new planning indicators is called the Block Time Overshoot (BTO). It is a planning indicator, so it does not describe performance of an individual flight movement on a particular day, but a number of flights: e.g. all the flights for the summer, or all the flights between two airports, or all flights with the same flight number.
BTO is the percentage of flights with an actual block time greater than the scheduled block time, i.e. flights with ATA – ATD > STA – STD (see the Glossary at the end of this document for definitions).
A high value of BTO means that a large proportion of these flights add delay between departure and arrival. This indicates a reduced delay recovery potential during the flight phase. If BTO = 100% then all actual block times exceeded the scheduled block time. A high BTO lowers predictability and increases arrival delays. Increased arrival delays will in turn result in increased reactionary delays. High BTO also means that a large percentage of flights had no capability to recover from delays on previous flights between Off-Block and On-Block.
A low value of BTO means that few flights add delay between departure and arrival. This increases the predictability of opera- tions and reduces arrival delays. Reduced arrival delays will also reduce reactionary delays. A low BTO indicates plenty of scope to recover from delay during the flight phase. If BTO = 0% then not a single flight had an actual block time exceeding the scheduled block time.
An advantage of BTO is that it is in principle not influenced by the departure punctuality of the flight1, so it allows the planner to focus on performance excluding reactionary delay. Analysis of CODA data indicates that the length of the delay at push- back has almost no influence on the length of the actual block time. Some rare cases show a slight increase in taxi-time for flights with long departure delays. So for this document, the influence of the departure punctuality on the BTO is considered to be neutral.
See Figure 13 for the percentage of flights delayed by more than 15 minutes on arrival (PDF-A). This figure increased from 17.2% in 2003 to 21.6% in 2008. The percentage of flights delayed by more than 15 minutes on departure increased from 16.3% in 2003 to 21.4% in 2008. During the same period the ratio of reactionary to primary delays increased from 0.57 to 0.83 meaning that not only was there a net increase in the percentage of flight being delayed, there was also an increase in flights delayed due to a reason not directly related to that flight.
1 Because the actual time of departure and the scheduled time of departure are both taken as starting points for the block-time measurement.
18 Planning for Delay: influence of flight scheduling on airline punctuality Trends in Air Traffic l Volume 7 25% 1.0
PDF-D>15 minutes 20% PDF-A>15 minutes 0.8
15% 0.6
10% 0.4
5% 0.2 Percentage of Delayed Flights of Delayed Percentage Ratio reactionary/primaryRatio delays
0% 0.0 2003 2004 2005 2006 2007 2008
Figure 13 - Yearly evolution of the Percentage of Delayed Flights (>15 minutes after Scheduled Time of Arrival/Departure) and the ratio of Reactionary to Primary delays during period 2003-2008.
This increased sensitivity of the European air transport system to primary delays could be explained by a reduction of the recovery potential during the flight and/or ground phase. Looking at the block-to-block phase we note that the BTO on European flights did not change significantly over recent years and remained stable at around 30% (see Figure 14).
These figures suggest that the increased sensitivity to primary delays is influenced by changes in the ground phase. More analysis is needed to determine the true cause. A joint study between RWTH Aachen University and Eurocontrol CODA looked at the drivers and impact of reactionary delays. The joint study points out that propagated (or reactionary delays) are very difficult to trace back to the original root cause, which is partially due to the lack of detail in the airline reporting of delays (e.g. aircraft rotational delays assigned to IATA delay code 93-RA account for 40% of departure delay minutes).
50%
40%
30% 31% 30% 30% 32% 32% 30% BTO 20%
10%
0% 2003 2004 2005 2006 2007 2008
Figure 14 - Yearly evolution of the BTO of the European Air Transport Network.
Planning for Delay: influence of flight scheduling on airline punctuality Trends in Air Traffic l Volume 7 19 For 2008, the BTO for all IFR flights in Europe was 30%. This means that 30% of flights had an actual block time that was longer than the scheduled block time and 70% of all flights had an actual block time that was lower or equal to the scheduled block time. This is a decrease of 2% compared to 2007 when the BTO was 32% resulting in a slightly increased buffer in the schedule to offset departure delays. A decrease of the BTO will have a positive effect on the arrival punctuality. Flights that departed without delay will most probably also arrive without delay.
The BTO is typically higher during the winter months compared with the summer months. See Figure 15 for an overview of monthly BTOs in 2007/2008. The lowest BTOs are observed during high summer. These differences between summer and winter months can be in excess of 10%.
Looking closer, the BTO is influenced by the strong seasonal variations of certain market segments. The weakest seasonal pattern in the BTO are observed on LCC flights (see Figure 16), with the lowest BTO reaching 21% and the highest BTO topping 28% (which is still below the European average of 30%).
The BTO on Traditional Scheduled flights (see Figure 17) varies between 27% and 36%. The highest variations in BTO can be observed on Charter flights (see Figure 18), with a monthly BTO between 31% and 47%.
Lower BTOs in summer can be explained by the fact that the average delay per movement and the percentage of delayed flights are higher during the summer months. Airlines may include a larger buffer in the schedules during the summer months to offset departure delays.
In summary, the BTO indicator can be used by airline scheduling, airline operational staff, airline punctuality analysts, airport slot coordinators and airport analysts, etc. The BTO indicator provides information on the schedule’s ability to limit arrival delays. The BTO varies around a 30% benchmark: if a planner sees a set of flights with BTO lower than 30%, this can indicate resources under-utilised; a BTO over 30% means a higher risk for arrival delays, and hence reactionary delays to the programme or network.
50%
40%
30% BTO 20%
10%
0% Jul-08 Jul-07 Oct-08 Oct-07 Jan-08 Jan-07 Jun-08 Jun-07 Apr-08 Apr-07 Feb-08 Feb-07 Dec-08 Dec-07 Sep-08 Sep-07 Nov-08 Nov-07 Mar-08 Mar-07 Aug-08 Aug-07 May-08 May-07
Figure 15 - 2007/2008 Monthly BTO for market segments LCC, Traditional Scheduled and Charter combined.
50% 20 Planning for Delay: influence of flight scheduling on airline punctuality Trends in Air Traffic l Volume 7
40%
30% BTO 20%
10%
0% Jul-07 Jul-08 Oct-07 Oct-08 Jan-07 Jan-08 Jun-07 Jun-08 Apr-07 Apr-08 Feb-07 Feb-08 Dec-07 Dec-08 Sep-07 Sep-08 Nov-07 Nov-08 Mar-07 Mar-08 Aug-07 Aug-08 May-07 May-08 50%
40%
30% BTO 20%
10%
0% Jul-07 Jul-08 Oct-07 Oct-08 Jan-07 Jan-08 Jun-07 Jun-08 Apr-07 Apr-08 Feb-07 Feb-08 Dec-07 Dec-08 Sep-07 Sep-08 Nov-07 Nov-08 Mar-07 Mar-08 Aug-07 Aug-08 May-07 May-08
50%
40%
30% BTO 20%
10%
0% Jul-07 Jul-08 Oct-07 Oct-08 Jan-07 Jan-08 Jun-07 Jun-08 Apr-07 Apr-08 Feb-07 Feb-08 Dec-07 Dec-08 Sep-07 Sep-08 Nov-07 Nov-08 Mar-07 Mar-08 Aug-07 Aug-08 May-07 May-08
Figure 16 - 2007/2008 Monthly BTO by market segment -LCC.
50%
40%
30% BTO 20%
10%
0% Jul-07 Jul-08 Oct-07 Oct-08 Jan-07 Jan-08 Jun-07 Jun-08 Apr-07 Apr-08 Feb-07 Feb-08 Dec-07 Dec-08 Sep-07 Sep-08 Nov-07 Nov-08 Mar-07 Mar-08 Aug-07 Aug-08 May-07 May-08
Figure 17 - 2007/2008 Monthly BTO by market segment –Traditional Scheduled.
50%
40%
50% 30% BTO 20%40%
10%30% BTO 20% 0%
10% Jul-07 Jul-08 Oct-07 Oct-08 Jan-07 Jan-08 Jun-07 Jun-08 Apr-07 Apr-08 Feb-07 Feb-08 Dec-07 Dec-08 Sep-07 Sep-08 Nov-07 Nov-08 Mar-07 Mar-08 Aug-07 Aug-08 May-07 May-08
Figure 18 - 2007/2008 Monthly BTO by market segment-Charter. 0% Jul-07 Jul-08 Oct-07 Oct-08 Jan-07 Jan-08 Jun-07 Jun-08 Apr-07 Apr-08 Feb-07 Feb-08 Dec-07 Dec-08 Sep-07 Sep-08 Nov-07 Nov-08 Mar-07 Mar-08 Aug-07 Aug-08 May-07 May-08
Planning for Delay: influence of flight scheduling on airline punctuality Trends in Air Traffic l Volume 7 21
50%
40%
30% BTO 20%
10%
0% Jul-08 Jul-07 Oct-08 Oct-07 Jan-08 Jan-07 Jun-08 Jun-07 Apr-08 Apr-07 Feb-08 Feb-07 Dec-08 Dec-07 Sep-08 Sep-07 Nov-08 Nov-07 Mar-08 Mar-07 Aug-08 Aug-07 May-08 May-07 5.2 Planner’s Indicator 2: Delay Difference Indicator-Flight (DDI-F)
“Delay Difference Indicator - Flight” is the difference between the arrival and departure punctuality expressed in minutes. Analysis of European delay data shows that on average the arrival delay is 3 minutes less than the departure delay, or a DDI-F of 3 minutes. This means that on average each flight has the potential to recover 3 minutes of delay.
The second new indicator is the Delay Difference Indicator – Flight (DDI-F) which is the difference between the arrival punc- tuality (ATA – STA) and the departure punctuality (ATD – STD) in minutes. The DDI-F expressed in minutes will give the delay saved or incurred between off-block and on-block. An optimum is achieved when the DDI-F is zero minutes, meaning that all resources have been used as planned. Airlines may usually opt to achieve a negative DDI-F to offset expected departure delays, moving away from the optimum scheduled block time in term of planned resources, but increasing predictability.
DDI-F = 0 Arrival Delay = Departure Delay DDI-F > 0 Arrival Delay > Departure Delay DDI-F < 0 Arrival Delay < Departure Delay
Example: A flight which has a 20 minutes departure delay and arrives with 30 minutes arrival delay will have a DDI-F of 10 minutes.
BTO and DDI-F both assess the robustness of the schedule, but where BTO counts flights, DDI-F measures minutes. BTO says how often there is a problem. DDI-F says how big the problem is in minutes. DDI-F can also be calculated for a single flight movement, so it is a measurement that can be shared with operational staff. Based on flights operated between airport-pairs with at least 1000 observed flights in 2008, Figure 19 clearly indicates the correlation between the BTO and the DDI-F, i.e. they are complementary ways of looking at the schedule’s ability to absorb or add delay. Negative DDI-F data on these airport pairs are obtained when the BTO drops below 40%.
5
0
-5 DDI-F
-10
-15 0% 10% 20% 30% 40% 50% 60% 70% BTO
Figure 19 - 2008 BTO and DDI-F by airport-pair (with at least 1000 observations). Each ‘x’ represents an airport-pair.
The DDI-F indicates the actual recovery potential in the schedule expressed in minutes. As seen before the average delay per movement on departure and arrival are almost identical in Europe (see Figure 11 on page 15), although differences by city-pair, aircraft type, season, etc. may occur. Airlines will try to reduce the increasing ratio of reactionary to primary delays (see Figure
5) by reducing arrival delays. Jan-07 Feb-07 Mar-07 Apr-07 May-07 Jun-07 Jul-07 Aug-07 Sep-07 Oct-07 Nov-07 Dec-07 Jan-08 Feb-08 Mar-08 Apr-08 May-08 Jun-08 Jul-08 Aug-08 Sep-08 Oct-08 Nov-08 Dec-08 0
-1
22 -2 Planning for Delay: influence of flight scheduling on airline punctuality Trends in Air Traffic l Volume 7 DDI-F -3
-4
-5 In Europe, arrival delays are mainly influenced by the departure punctuality. The easiest way to improve arrival punctuality is by improving the departure punctuality. If this cannot be achieved, airlines may opt to include a buffer time in the schedule to neutralise these departure5 delays and reduce the knock-on effect on the network (reactionary delays caused by late incoming aircraft, passengers or crew).
The Average Delay per Movement0 for both Departures and Arrivals is lower in winter compared with the summer months. The gap between the average departure and arrival delay per movement is at its peak during the summer months with lower arrival delays compared with departure delays (see Figure 11 on page 15). -5 In 2008 IFR flights operatedDDI-F in Europe had an average DDI-F of -3.0 minutes. This indicates an improvement of the arrival punctuality compared to the departure punctuality. The DDI-F did not change significantly compared to 2007 when the DDI-F was -2.9 minutes. -10
An average DDI-F of -3.0 minutes in Europe cannot be seen as large-scale schedule padding by airlines, because it includes, for example, the efforts on-15 the operational day of the crew and operations staff to catch up for earlier delays. In practice, it will be a very difficult task to achieve a neutral DDI-F of zero minutes, which is also the economic optimum. Airlines will therefore 0% 10% 20% 30% 40% 50% 60% 70% play on the safe side with a slightly negative DDI-F in order to reduce their arrival delays. BTO Figure 20 gives an overview of the monthly evolution of the DDI-F in Europe. The DDI-F is typically lower during summer months when longer departure delays occur. The lowest DDI-F in 2007 was observed during August when it reached -3.94 minutes. In 2008, the lowest DDI-F also occurred in August but slightly higher at -3.81 minutes. Jan-07 Feb-07 Mar-07 Apr-07 May-07 Jun-07 Jul-07 Aug-07 Sep-07 Oct-07 Nov-07 Dec-07 Jan-08 Feb-08 Mar-08 Apr-08 May-08 Jun-08 Jul-08 Aug-08 Sep-08 Oct-08 Nov-08 Dec-08 0
-1
-2 DDI-F -3
-4
-5
Figure 20 - 2007/2008 Monthly DDI-F.
Looking at the monthly BTO and DDI-F during 2007/2008 we observe a correlation between these two indicators. A low BTO will also generate a low DDI-F (see Figure 21). The lowest BTO and DDI-F are observed in August .
Looking at the monthly BTO and DDI-F by market segments (see Figure 22, Figure 23 & Figure 24) we can observe that the lowest monthly BTO also had the lowest DDI-F (BTO of 21% and DDIF of -6.0 minutes, market segment LCC’s in August 2007, see Figure 22).
Planning for Delay: influence of flight scheduling on airline punctuality Trends in Air Traffic l Volume 7 23 BTO DDI-F 60% 2
50% 0
40% -2
30% -4
20% -6
10% -8 On the other hand, the highest BTO was linked to the highest DDI-F observed (BTO of 47% and DDI-F of +0.4, market segment Jul-07 Jul-08 Oct-07 Oct-08 Jan-07 Jan-08 Jun-07 Jun-08 Apr-07 Apr-08 Feb-07 Feb-08 Dec-07 Dec-08 Sep-07 Sep-08 Nov-07 Nov-08 Mar-07 Mar-08 Aug-07 Aug-08 May-07 Charter in February 2008, see Figure 23 & Figure 24). This clearly demonstrates that there is no recovery potentialMay-08 in the schedule, because even if a flight leaves on-time (zero delay minutes) it will arrive after the scheduled time of arrival.
BTO DDI-F BTO DDI-F 60% 2 60% 2 BTO DDI-F 50% 0 60%50% 02
40% -2 50%40% -20
30% -4 40%30% -4-2
20% -6 30%20% -6-4
10% -8 20%10% -8-6 Jul-08 Jul-07 Oct-08 Oct-07 Jan-08 Jan-07 Jun-08 Jun-07 Apr-08 Apr-07 Feb-08 Feb-07 Dec-08 Dec-07 Sep-08 Sep-07 Nov-08 Nov-07 Mar-08 Mar-07 Aug-08 Aug-07 Jul-08 Jul-07 May-08 May-07 Oct-08 Oct-07 Jan-08 Jan-07 Jun-08 Jun-07 Apr-08 Apr-07 Feb-08 Feb-07 Dec-08 Dec-07 Sep-08 Sep-07 Nov-08 Nov-07 Mar-08 Mar-07 Aug-08 Aug-07 May-08 May-07 10% -8
Figure 21 - 2007/2008 Monthly BTO & DDI-F for market Figure 22 - 2007/2008 Monthly BTO & DDI-F Jul-08 Jul-07 Oct-08 Oct-07 Jan-08 Jan-07 Jun-08 Jun-07 Apr-08 Apr-07 Feb-08 Feb-07 Dec-08 Dec-07 Sep-08 Sep-07 Nov-08 Nov-07 Mar-08 Mar-07 Aug-08 Aug-07 May-08 segments LCC, Traditional Scheduled and Charter combined. May-07 by market segment –LCC.
BTO DDI-F 60% 2 BTO DDI-F BTO DDI-F 50%60% 20 60% 2
40%50% 0-2 50% 0
30%40% -2-4 40% -2
20%30% -4-6 30% -4
10%20% -6-8 20% -6 Jul-08 Jul-07 Oct-08 Oct-07 Jan-08 Jan-07 Jun-08 Jun-07 Apr-08 Apr-07 Feb-08 Feb-07 Dec-08 Dec-07 Sep-08 Sep-07 Nov-08 Nov-07 Mar-08 Mar-07 Aug-08 Aug-07 May-08 10% May-07 -8 10% -8 Jul-08 Jul-07 Jul-08 Jul-07 Oct-08 Oct-07 Jan-08 Jan-07 Jun-08 Jun-07 Apr-08 Apr-07 Feb-08 Feb-07 Dec-08 Dec-07 Sep-08 Sep-07 Nov-08 Nov-07 Oct-08 Oct-07 Jan-08 Jan-07 Mar-08 Mar-07 Aug-08 Aug-07 Jun-08 Jun-07 Apr-08 Apr-07 Feb-08 Feb-07 Dec-08 Dec-07 May-08 May-07 Sep-08 Sep-07 Nov-08 Nov-07 Mar-08 Mar-07 Aug-08 Aug-07 May-08 May-07
Figure 23 - 2007/2008 Monthly BTO & DDI-F Figure 24 - 2007/2008 Monthly BTO & DDI-F by market segment –Traditional Scheduled. by market segment – Charter.
BTO DDI-F 60% 2
50% 0
40% -2
30% -4 24 Planning for Delay: influence of flight scheduling on airline punctuality Trends in Air Traffic l Volume 7 20% -6
10% -8 Jul-07 Jul-08 Oct-07 Oct-08 Jan-07 Jan-08 Jun-07 Jun-08 Apr-07 Apr-08 Feb-07 Feb-08 Dec-07 Dec-08 Sep-07 Sep-08 Nov-07 Nov-08 Mar-07 Mar-08 Aug-07 Aug-08 May-07 May-08 5.3 Example: Indicators for flights on Frankfurt to Istanbul route
To illustrate the new indicators that were introduced in the previous two sections, this section discusses the schedule planning for a single airport pair using the BTO & DDI-F.
Figure 25 shows the evolution of scheduled block times on the Frankfurt (EDDF) to Istanbul (LTBA) route in 2007/2008 (which includes IATA seasons W06-S07-W07-S08). Only traditional scheduled flights operated by narrow-body jets (A319/20/21 & B737-800) were taken into account. These aircraft have similar performance and cruising speeds. Other categories like charter, cargo or LCC represent less than 2% of observed traffic on this airport pair and were ignored.
During the observed period, four scheduled times were observed: 155, 165, 175 and 180 minutes. One historical flight has a constant scheduled block time of 165 minutes between November 2006 and October 2008. From January 2008, a new flight was operated with a scheduled block time of 155 minutes.
In the background of Figure 25 are lines showing the distribution of the actual block times indicated by the mid-point (median) and two extreme percentile values (5th and 95th percentile). Over the observed period the monthly median of the actual block times remained stable at around 170 minutes. The other percentiles are also variable, but around a constant level, so that only 5% of flights typically made the trip in under 150 minutes. These actual times would only change if the aircraft type, the route, wind or the taxi times were to change. Of the percentile lines, it’s the 95th percentile which is most variable.
To link the actual data directly to choice of scheduled block time, Figure 26 shows the aggregate data per scheduled block time. Since the actual times are stable during these two years, we can aggregate over the whole time period. A scheduled block time of 155 minutes results in a 71% BTO and a DDI-F of +6 minutes. This means that 71% of flights had an actual block time exceeding 155 minutes and the average delay per movement on arrival was 6 minutes longer than on departure, or a difference in BTO of 41 percentage points and DDI-F of 9 minutes compared to the European average of 30% BTO and a DDI-F of –3 minutes in 2008.
Those flights with a BTO around 30% (flights with a scheduled block time of 165 & 180 minutes) were able to improve their arrival punctuality during the flight phase. Flights with a BTO above 50% saw a significant decrease in the arrival punctuality (+ 6 minutes average arrival delay compared to the departure delay).
Figure 26 shows that increasing the block time will not always lead to a reduction in BTO and DD-F. The block time should be related to the aircraft type, time of operation and route flown or it will not lead to the expected result. An example is the lower BTO on flights with a block time of 165 minutes compared to flights with a block time of 175 minutes.
Flights with a block time of 180 minutes had a BTO of 30% and DDI-F of -4 minutes which is almost equal to the European average for 2008. The average arrival delay was reduced by 4 minutes compared to the departure delay.
Figure 27 indicates the DDI-F for the various scheduled block times on the Frankfurt to Istanbul route. The shortest block time of 155 minutes has no recovery potential in the schedule with more than 70% of flights adding delays during the flight stage.
Planning for Delay: influence of flight scheduling on airline punctuality Trends in Air Traffic l Volume 7 25 Whilst short (=< 15 minutes) departure delays on the ground (engines off) will not have a huge financial influence on the airline operational results, delays longer than 15 minutes are estimated at €82 per minute on average (2008 prices)1.
If a flight with a scheduled block time of 155 minutes is unable to make up some of the arrival delay during the ground phase, the next flight will most probably suffer a reactionary delay of 30 minutes2. This will result in an operational cost of 30 minutes x €82/minute= €2460 for each flight. If this is a daily service the potential financial impact on the operational result of the airline is excessively high. A future issue of Trends in Air Traffic will take a closer look at reactionary delays and their propagation through the network.
210
200
190
180 Block Time Block 170
160 Actual Block time_5% 150 Actual Block time_Median Actual Block time_95% Scheduled Block time 140 Jan07 Apr07 Jul07 Oct07 Jan08 Apr08 Jul08 Oct08 Jan09
Figure 25 - Scheduled Block time evolution on flights from Frankfurt to Istanbul-Ataturk during 2007/2008 (A319/320/321 & B738’s)
1 See PRR2009, Performance Review Report, An Assessment of Air Traffic Management in Europe, during the Calendar Year 2009, 20 May 2010 (Chapter 9). A digital copy is available on www.eurocontrol.int/prc 2 Flights with a scheduled block time of 155 minutes show a mean arrival delay of 30 minutes.
26 Planning for Delay: influence of flight scheduling on airline punctuality Trends in Air Traffic l Volume 7 Scheduled 5th 10th 90th 95th Block time BTO DDI-F Variable Mean Ptcl Pctl Median Pctl Pctl
Dep.delay 24 4 7 17 47 67 155 Mins 71% + 6 mins Arr. delay 30 6 9 23 60 72
Dep.delay 15 -3 0 11 34 48 165 Mins 36% - 2 mins Arr. delay 13 -8 -4 9 34 49
Dep.delay 19 -5 -1 10 52 70 175 Mins 66% + 3 mins Arr. delay 23 -10 -7 16 57 76
Dep.delay 24 0 0 18 51 70 180 Mins 30% - 4 mins Arr. delay 20 -9 -6 13 52 66
Figure 26 - Influence of Scheduled Block time on Arrival Punctuality on flights from Frankfurt to Istanbul-Ataturk. (A319/320/321 & B738’s)
30
20
10
0 DDI-F
-10
-20
-30 155 160 165 170 175 180 Scheduled Block Time
Figure 27 - Influence of Scheduled Block time on DDI-F on flights from Frankfurt to Istanbul-Ataturk. (A319/320/321 & B738’s) (Box represents 25th percentile low, 75th high and whisker represents 5th percentile low and 95th percentile high)
Planning for Delay: influence of flight scheduling on airline punctuality Trends in Air Traffic l Volume 7 27
6. vARIABLES INFLUENCING A FLIGHT SCHEDULE
Operating in an open (internal) market, airlines have the freedom of choice regarding the schedule or timetable they publish. In practice there will be numerous variables influencing this schedule. The single most important factor in the choice of a sche- dule is the choice of city-pair: which two airports will be linked with an air service? The choice of airport pair has an influence on the choice of aircraft type, flight time (distance), taxi-times and many other variables.
In this section we take a closer look at some of the variables that have an influence on the scheduled block time:
Airport Pair see section 6.1
Opening hours of airport (e.g. night curfew times) see section 6.2
Operational aspects (e.g. availability of crew, airframe, flight and duty time limitations etc) see section 6.3
Taxi-times see section 6.4
Operating Speed (fixed Mach-speed or Cost Index) see section 6.5
Winds aloft see section 6.6
Time of Operation see section 6.7
30 Planning for Delay: influence of flight scheduling on airline punctuality Trends in Air Traffic l Volume 7 6.1 Airport Pair by Level of Airport Slot Coordination
The choice of airport of departure and airport of destination is the single most important driver in airline scheduling and influences the choice of airframe, which in turn, determines the length of the flight phase. In this section we take a closer look at airport slots. Airlines will have to apply for an airport slot when they schedule to depart or arrive at an airport with capacity constraints.
Airports are divided into three categories to identify their capacity level: non-coordinated, schedule facilitated and coordinated. The level of coordination is set for an IATA season but changes in category depending on the type of flight or day of the week may occur in specific cases. See the glossary for definitions of airport slots and levels of airport slot coordination.
On 21 April 2004 the European Parliament and the Council adopted Regulation (EC) No 793/20041 amending Council Regulation No95/93 on common rules for the allocation of slots2 at Community airports. This regulation aims to stimulate a better use of scarce capacity at congested and coordinated Community airports. The EC slot regulation is mainly based on IATA guidelines (IATA Worldwide Scheduling Guidelines).
Three categories of airports can be identified:
Level 1: non-coordinated airport. An airport where the capacity of all the systems at the airport is adequate to meet the demand of the users.
n Direct discussions between Airline, Airport and Handling Agent
Level 2: schedules facilitated airport. An airport where there is potential for congestion at some periods of the day, week or scheduling period which is amenable to resolution by voluntary cooperation between airlines and where a schedules facilitator has been appointed to facilitate the operations of airlines conducting services at that airport or intending to operate services at that airport.
n Discussions between Airport and Airline via the Schedules Facilitator
Level 3: coordinated airport. An airport where the expansion of the capacity, in the short term, is highly improbable and congestion is at such high level that:
n The demand of the airport infrastructure exceeds availability during the relevant period
n Attempts to resolve problems through voluntary schedule changes have failed
n Airlines must have been allocated slots before they can operate to that airport
n Discussions between Airport and Airline via the Coordinator. Level 3 airports must have an independent coordinator who’s activities must be neutral, transparent and non-discriminatory
1 Regulation (EC) No 793/2004 of the European Parliament and the Council of 21 April 2004 (OJ L 138, 30.04.2004, p.50) amending Council Regulation (EEC) No95/93 of 18 January 2003 on common rules for the allocation of slots at Community Airports (OJ L 14, 22.01.1993). 2 Slot means the permission given by the coordinator in accordance with Regulation EC No 793/2004 to use the full range of airport infrastructure necessary to operate an air service at a coordinated airport on a specific date and time for the purpose of landing or take-off as allocated by a coordinator in accordance with Regulation EC No 793/2004.
Planning for Delay: influence of flight scheduling on airline punctuality Trends in Air Traffic l Volume 7 31 IATA’s Worldwide Scheduling Guidelines definition of an airport slot is:
Airport Slot (§ 5.3 WSG 16th edition): “A (airport) slot is defined as the scheduled time of arrival or departure available for allocation by, or as allocated by, a coordinator for an aircraft movement on a specific day at a coordinated airport. For scheduling purposes, the (airport) slot is the scheduled time of arrival or departure at the terminal, not the time of landing or take-off from the runway.
Traffic concentrated at big airports
Looking at flights it can be observed that 75% of airports in Europe (see Figure 28) have fewer than 1000 IFR departures a year. 25% of airports generate 98% of the IFR traffic. Looking closer at those airports with > 100 000 flights in 2008 we observe that the 15 airports which had between 100 000 -200 000 IFR departures generated 21% of total traffic. There were six airports with > 200 000 departures in 2008 and they generated 16% of total departures. The 25 largest airports in Europe generate 41% of traffic1 (see Figure 29).
Airport Class Number of Airports in this (Total IFR Departures 2008) Class <1K 1524 1k-2K 109 2k-5k 161 5k-10k 84 10k-20k 54 20k-50k 64 50k-100k 23 100k-200k 15 >200k 6 Figure 28 - Airport Class by Total IFR Departures in 2008.
2% 2% 6% 16% 7%
8%
Total IFR <1K Departures 1k-2K by Airport 2k-5k Class 2008 5k-10k 10k-20k 20k-50k 50k-100k 21% 100k-200k >200k 20%
16%
Figure 29 - Total IFR Departures in 2008 by Airport Class.
1 A Place to Stand: Airports in the European Air Network, EUROCONTROL trends in Air Traffic Volume 3, 3 September 2007 (Section 3).
32 Planning for Delay: influence of flight scheduling on airline punctuality Trends in Air Traffic l Volume 7 IATA’s Worldwide Scheduling Guidelines (16th edition) includes 57 schedules facilitated airports (level 2) and 94 Coordinated Airports (level 3) in Europe. This means that out of the 2040 European airports which generated IFR traffic (2008 figures) 92.6% of airports had no capacity problems (level 1), 2.8% of airports had the potential for congestion (level 2) and 4.6% of airports had capacity constraints (level 3). All airlines operating to these 94 level 3 airports which have capacity constraints during most of the year will need to apply for an airport slot before they can operate a flight (see Figure 30).
4,6% 2,8%
4,6% 2,8% Level 1 Level 2 Level 3
Level 1 Level 2 92,6% Level 3
Figure 30 - 2008 European airports by Level of Coordination based on IATA WSG16th edition3.
European Departures 92,6%
Looking at the share of European flights61% by level of airport coordination24% (for market segments LCC, traditional scheduled and charter) we observe that 24% of flights depart from an airport with no capacity problem, 15% of flights depart from an airport which is schedule facilitated and 61% of all flights depart from a coordinated airport.
61% 24% Level 1 Level 2 Level 3
Level 1 15% Level 2 Level 3
15%
Figure 31 - 2008 Total European departures by airport Level of Coordination based on IATA WSG16th edition for market segments LCC, Traditional Scheduled and Charter.
1 WSG 16th edition, IATA Worldwide Scheduling Guidelines, effective July 2008. www.iata.org 2 Level of airport coordination may change depending on season, day of week or type of flight. 3 IATA WSG16: IATA Worldwide Scheduling Guidelines – Effective July 2008.
Planning for Delay: influence of flight scheduling on airline punctuality Trends in Air Traffic l Volume 7 33 All Flights in Europe
Looking at the airport pairs (European and non-European airports) based on the level of coordination of the airport of depar- ture and the airport of destination we observe nine possible combinations. Each combination has a different level of difficulty in trying to streamline the scheduled time of departure and scheduled time of arrival to an optimum scheduled block time.
The easiest combination for an airline scheduler will be linking an airport of Level 1 with another airport of Level 1. In this case there is no need to request an airport slot. However, this is a rare combination: in 2008 only 7% of European IFR flights were operated between Level 1 airports.
The most difficult combination for an airline scheduler will be linking an airport of Level 3 with another airport of Level 3. An airline will have to apply for an airport slot at the airport of departure and the airport of destination. In 2008, 37% of European IFR flights were operated between Level 3 airports (see Figure 32).
In 2008, 85% of European IFR flights were operated between airport pairs with at least one Level 3 airport in the combination. This means that 85% of all IFR flights in Europe were subject to at least one airport slot at either the airport of departure or at the destination airport. Aircraft operators are faced with a very complex task setting an optimum schedule caused by the scarce availability of airport slots. The percentage of flights that are subject to an airport slot will increase even further as mentioned in Challenges of Growth 2008.1
Challenges of Growth 2008: “In the most-likely scenario in 2030, 19 airports will be operating at full capacity eight hours a day, every day of the year, and involving 50% of all flights each day. In the most challenging scenario, 39 airports would be at full capacity, involving 70% of flights on departure or arrival or both.”
2% 20% 37%
Coordinated Schedules Facilitated Level 3 Level 2
28% 6%
7%
Non- Coordinated Level 1
Figure 32 - 2008 Proportion of IFR flights linking Coordinated, Schedules Facilitated and Non-Coordinated airports.
1 Challenges of Growth 2008, EUROCONTROL, November 2008, www.eurocontrol.int/statfor
34 Planning for Delay: influence of flight scheduling on airline punctuality Trends in Air Traffic l Volume 7 An airline will have to make a balance between an optimum schedule and the availability of airports slots when operating at a coordinated airport. This may cause schedule differences within the same city-pair.
Note that an air carrier’s flight plan may be rejected by the competent Air Traffic Management authorities if the air carrier intends to land or take off at a coordinated airport, during the periods1 for which it is coordinated, without having a slot allocated by the coordinator. This will increasingly be true in the future.
BTO & DDI-F by Level of Coordination
Differences in the BTO and DDI-F could determine if block times are influenced by the level of coordination at the airport of departure or arrival. The example of flights operated from Frankfurt to Istanbul (both level 3 airports) already indicated that airlines may operate with non-optimal scheduled block times which in its turn will influence the arrival punctuality.
Figure 33 gives an overview of the BTO and DDI-F on airport pairs grouped by the level of coordination of that airport. In 2008, the highest BTO was observed on flights linking level 3 airports, whereas the lowest BTO can be seen on flights operated from level 2 to level 1 airports. The highest DDI-F is seen on flights linking level 1 airports, and the lowest (i.e. largest recovery ability) on flights operated between level 2 airports. Notice also that the BTO is higher flying from level 2 to level 3 airports, compared to flights operated from level 3 to level 2 airports.
Two clusters of airports can be observed in Figure 33 . Flights to/from level 2 airports seem to have a significant lower BTO and DDI-F then flights operated to/from level 3 airports. These differences are likely to be influenced by the different scheduling techniques for each market segment. In this example level 1 and level 3 airports handle mainly scheduled flights (between 75% and 80% of traffic) whilst level 2 airports accommodate mostly low-cost flights (56% of traffic).
To give an idea of the variation in BTO and DDI-F we take three examples: airport pairs which link airports with identical level of coordination (3-3, 2-2 & 1-1).
0,0 Level of Slot Coordination BTO DDI-F -0,5 (ADEP-ADES) -1,0 1-1 26% -2,57 -1,5 1-2 24% -3,58 -2,0 1-3 30% -2,71 2-1 23% -3,95 DDI-F -2,5 3-1 1-1 1-3 3-3 2-2 24% -4,13 -3,0 2-3 29% -3,31 3-2 2-3 -3,5 1-2 3-1 30% -2,67 -4,0 2-1 3-2 27% -3,37 2-2 -4,5 3-3 31% -2,86 20% 25% 30% 35% 40% BTO
Figure 33 - 2008: BTO & DDI-F on City-pairs by Level of Coordination.
1 The level of airport slot coordination may vary depending on the type of flight, IATA season, or day of week.
Planning for Delay: influence of flight scheduling on airline punctuality Trends in Air Traffic l Volume 7 35 Coordinated to Coordinated (Level 3 to Level 3)
The BTO of flights operated between Coordinated and Coordinated airports was 30.4% in 2008 compared to 31.9% in 2007. The lowest monthly BTO in 2008 was recorded in August when the BTO reached 26.8%, compared to 27.8% during the same month in 2007 (see Figure 34).
The DDI-F remained stable during 2008 and 2007 at -3 minutes which is equivalent to the 2008 European DDI-F for all IFR flights. The lowest monthly DDI-F’s were also recorded during the summer months. The DDI-F dropped to -3.8 minutes in August 2008 compared to -3.9 minutes in August 2007 (see Figure 35).
Observation: In 2008 traffic between level 3 airports represented 37% of all IFR traffic in Europe. The BTO and DDI-F almost equalled the European average of 30% BTO and a DDI-F of -3 minutes and the monthly pattern is almost identical to overall traffic at European level (Traditional scheduled, Charter and LCC combined). 40%
40%35%
35%30% BTO
30%25% BTO 20% 25%
20%15% Jul-07 Jul-08 Oct-07 Oct-08 Jan-07 Jan-08 Jun-07 Jun-08 Apr-07 Apr-08 Feb-07 Feb-08 Dec-07 Dec-08 Sep-07 Sep-08 Nov-07 Nov-08 Mar-07 Mar-08 Aug-07 Aug-08 May-07 May-08 15% Jul-07 Jul-08 Oct-07 Oct-08 Jan-07 Jan-08 Jun-07 Jun-08 Apr-07 Apr-08 Feb-07 Feb-08 Dec-07 Dec-08 Sep-07 Sep-08 Nov-07 Nov-08 Mar-07 Mar-08 Aug-07 Aug-08 May-07 May-08
Figure 34 -Monthly BTO of flights operated between Coordinated and Coordinated airports.
5 4
53 42 31 20 DDI-F -11 -20 DDI-F -1-3 -2-4 -3-5 -4 Jul-07 Jul-08 Oct-07 Oct-08 Jan-07 Jan-08 Jun-07 Jun-08 Apr-07 Apr-08 Feb-07 Feb-08 Dec-07 Dec-08 Sep-07 Sep-08 Nov-07 Nov-08 Mar-07 Mar-08 Aug-07 Aug-08 May-07 May-08 -5 Figure 35 - Monthly DDI-F of flights operated between Coordinated and Coordinated airports. Jul-07 Jul-08 Oct-07 Oct-08 Jan-07 Jan-08 Jun-07 Jun-08 Apr-07 Apr-08 Feb-07 Feb-08 Dec-07 Dec-08 Sep-07 Sep-08 Nov-07 Nov-08 Mar-07 Mar-08 Aug-07 Aug-08 May-07 May-08
36 Planning for Delay: influence of flight scheduling on airline punctuality Trends in Air Traffic l Volume 7 Schedules Facilitated to Schedules Facilitated (Level 2 to Level 2)
The BTO of flights operated between Schedules Facilitated and Schedules Facilitated airports was 24.2% in 2008 compared to 22.8% in 2007. The lowest monthly BTO in 2008 was recorded in August, when the BTO reached 21.4%, compared to 19.6% during the same month in 2007 (see Figure 36).
The DDI-F decreased from -4.52 minutes in 2007 to -4.05 minutes in 2008. The lowest monthly DDI-F’s were also recorded during the summer months. The DDI-F in August 2007 was -5.41 minutes compared to -4.72 minutes during the same month in 2008. One exception is April 2007 when the DDI-F reached -5.57 minutes. The increase in April 2007 could be explained by the “holiday effect” around Easter which is also observed during the summer months. Airlines will apply slightly longer scheduled block times to offset departure delays (see Figure 37).
Observation: In 2008 traffic between level 2 airports represented 2% of all IFR traffic in Europe. The BTO was 6% lower than the Euro- pean average of 30%. The DDI-F40% was one minute lower than the European average of -3 minutes.
35% 40%
30% 35% BTO 25% 30%
BTO 20% 25%
20%15% Jul-07 Jul-08 Oct-07 Oct-08 Jan-07 Jan-08 Jun-07 Jun-08 Apr-07 Apr-08 Feb-07 Feb-08 Dec-07 Dec-08 Sep-07 Sep-08 Nov-07 Nov-08 Mar-07 Mar-08 Aug-07 Aug-08 May-07 May-08 15% Jul-07 Jul-08 Oct-07 Oct-08 Jan-07 Jan-08 Jun-07 Jun-08 Apr-07 Apr-08 Feb-07 Feb-08 Dec-07 Dec-08 Sep-07 Sep-08 Nov-07 Nov-08 Mar-07 Mar-08 Aug-07 Aug-08 May-07 May-08
Figure 36 - Monthly BTO of flights operated between Schedules Facilitated and Schedules Facilitated airports.
5 4 3 2 51 40 -13 -22 1
DDI-F -3 -40 -1-5 -2-6
DDI-F -3-7 -4-8 -5-9 -10-6 -7 -8 Jul-07 Jul-08 Oct-07 Oct-08 Jan-07 Jan-08 Jun-07 Jun-08 Apr-07 Apr-08 Feb-07 Feb-08 Dec-07 Dec-08 Sep-07 Sep-08 Nov-07 Nov-08 Mar-07 Mar-08 Aug-07 Aug-08 May-07 -9 May-08 -10 Figure 37 - Monthly DDI-F of flights operated between Schedules Facilitated and Schedules Facilitated airports. Jul-07 Jul-08 Oct-07 Oct-08 Jan-07 Jan-08 Jun-07 Jun-08 Apr-07 Apr-08 Feb-07 Feb-08 Dec-07 Dec-08 Sep-07 Sep-08 Nov-07 Nov-08 Mar-07 Mar-08 Aug-07 Aug-08 May-07 May-08
Planning for Delay: influence of flight scheduling on airline punctuality Trends in Air Traffic l Volume 7 37 Non-Coordinated to Non-Coordinated (Level 1 to Level 1)
The BTO of flights operated between Non-Coordinated and Non-Coordinated airports was 30.3% in 2008 compared to 38.9% in 2007. The lowest monthly BTO in 2008 was recorded in June when the BTO reached 24.7%, compared to 36.9% during the same month in 2007 (see Figure 38).
An explanation for the drop in BTO could be found in the drop of re-routings to avoid en-route ATFCM regulations. The BTO is sensitive to flight efficiency: flights which were not re-routed will have a lower BTO compared to those that flew longer to avoid en-route restrictions. 45%
Note that pre-departure delays, such as ATFCM en-route restrictions,40% will not have an influence on the BTO nor the DDI-F.
The annual DDI-F did not change much between 2008 and 2007,35% from -1.89 minutes in 2007 to -1.88 minutes in 2008. The lowest monthly DDI-F was recorded in June 2008 when the DDI-F reached -2.67 minutes down from -1.81 during June 2007. BTO 30%
Observation: In 2008 traffic between level 1 airports represented 7% of25% all European IFR traffic. The BTO was identical to the European average of 30%. At -1.9 minutes the DDI-F was 1.1 minute higher than the European average of -3 minutes. 20%
15% Jul-08 Jul-07 Oct-08 Oct-07 Jan-08 Jan-07 Jun-08 Jun-07 Apr-08 Apr-07 Feb-08 Feb-07 Dec-08 Dec-07 Sep-08 Sep-07 Nov-08 Nov-07 Mar-08 Mar-07 Aug-08 Aug-07 May-08 May-07
45% 5 4 40% 3
35% 2 1
BTO 30% 0 DDI-F -1 25% -2 20% -3 -4 15% -5 Jul-07 Jul-08 Jul-07 Jul-08 Oct-07 Oct-08 Jan-07 Jan-08 Jun-07 Jun-08 Apr-07 Apr-08 Feb-07 Feb-08 Dec-07 Dec-08 Sep-07 Sep-08 Oct-07 Oct-08 Jan-07 Jan-08 Nov-07 Nov-08 Jun-07 Jun-08 Apr-07 Apr-08 Mar-07 Mar-08 Aug-07 Aug-08 Feb-07 Feb-08 Dec-07 Dec-08 Sep-07 Sep-08 May-07 May-08 Nov-07 Nov-08 Mar-07 Mar-08 Aug-07 Aug-08 May-07 May-08
Figure 38 - Monthly BTO of flights operated between Figure 39 -Monthly DDI-F of flights operated between Non-Coordinated and Non-Coordinated airports Non-Coordinated and Non-Coordinated airports
5 4 3 2 1 0 DDI-F -1 38 Planning for Delay: influence of flight scheduling on airline punctuality Trends in Air Traffic l Volume 7 -2 -3 -4 -5 Jul-07 Jul-08 Oct-07 Oct-08 Jan-08 Jan-07 Jun-07 Jun-08 Apr-07 Apr-08 Feb-08 Feb-07 Dec-07 Dec-08 Sep-07 Sep-08 Nov-07 Nov-08 Mar-07 Mar-08 Aug-07 Aug-08 May-07 May-08 6.2 Airport opening hours
Airport opening hours strongly influence schedules. Airlines will not be allowed to schedule flights to depart or arrive outside the normal opening hours of an airport. Bunching of departures at the end of a night curfew can create an overload in demand and consequently cause delays which propagate throughout the day.
Airport opening hours have a determining effect on airline schedules. Airlines will not be able to schedule a departure or arrival outside the opening hours of the airport (regardless of the level of coordination). In order to maximise the utilisation of resources, airlines may schedule departures at the very moment of the opening of the airport (or even slightly before). There might even be so many departures at that moment that these head start delays propagate through the day and the complete network.
Airlines might plan some flights to depart right at the opening of the airport but will allow some buffer time for the scheduled arrivals prior to the night curfew or closure of the airfield. Düsseldorf (EDDL) is a good example of an airport with heavy traffic right at the end of the night curfew (see Figure 40). London-City (EGLC) (see Figure 42) and Stockholm-Bromma (ESSB) airports are examples of airports where airlines take some buffer at the end of the day to allow all aircraft to leave these airports and return to their home bases prior to the closure of the airport.
Taking Düsseldorf (EDDL) as an example (see Figure 40) of an airport which operates 24 hours a day but where local noise abatement prevents take off prior to 0600 local time (LT). Aircraft operators can file an estimated off-blocks time (EOBT1) 10 minutes prior to the end of the noise abatement. Flights are not allowed to take-off prior to the end of the night ban, but aircraft can already taxi out to the threshold and be ready for a take-off at exactly 0600 local time.
20 Night Night Curfew Curfew
15
10
5
Planned departures intervals) (30 minutes 0 2:30:00 3:00:00 3:30:00 3:50:00 4:00:00 4:30:00 5:00:00 5:30:00 6:00:00 6:30:00 7:00:00 7:30:00 8:00:00 8:30:00 9:00:00 9:30:00 10:00:00 10:30:00 11:00:00 11:30:00 12:00:00 12:30:00 13:00:00 13:30:00 14:00:00 14:30:00 15:00:00 15:30:00 16:00:00 16:30:00 17:00:00 17:30:00 18:00:00 18:30:00 19:00:00 19:30:00 20:00:00 20:30:00 21:00:00 21:30:00 22:00:00 22:30:00 Scheduled Time of Departure (UTC)
Figure 40 - Düsseldorf Airport (EDDL). Distribution of flights on July 04, 2008 based on IOBT2.
1 EOBT: Estimated Off-Block Time, estimated or planned time at which the aircraft will leave the stand. 2 IOBT: IFPS Off-Block Time, last known EOBT within IFPS. All aircraft operators must send a flight plan with an Instrument Flight Rules (IFR) component for flights operated within the Initial Plan Processing System (IFPS) airspace to the EUROCONTROL CFMU IFPS service.
Planning for Delay: influence of flight scheduling on airline punctuality Trends in Air Traffic l Volume 7 39 The concentration of flights leaving at the opening of the airport translates into an increase of local departure restrictions (IATA delay code 89/AM1) during these peaks (see Figure 41). Looking at departures from Düsseldorf on July 04, 2008 grouped in 30 minutes intervals we see that the majority of delays due to local airport restrictions occur right at the opening of the airport and shortly after when the total departures peak at 18 aircraft in the 30 minutes between 0430-0459UTC. In the period between 0430-0500UTC 12% of daily delay code 89 are assigned with an average delay of 2.9 minutes per movement (compared to an average of 0.05 minutes delay per movement caused by delay code 89 for all movements in 2008).
18%
16%
14%
12%
10%
8%
6%
4%
2%
% of Daily delaycodes 89 (by 30 mins interval) 89 (by % of Daily delaycodes 0% 03:00 05:00 07:00 09:00 11:00 13:00 15:00 17:00 19:00 21:00 23:00 UTC
Figure 41 - Percentage of total daily delays caused by “Restrictions at Airport of Departure” (IATA delay code 89) at Düsseldorf Airport (EDDL) by 30 minute intervals starting at 03:30. The size of the bubble indicates the sum of the delay minutes. The average delay per delay code 89 peaks at 9.4 minutes between 0500-0529UTC when 14% of delay code 89 on that day were assigned. So in that first hour, a quarter of the day’s delay has been incurred. Flights that suffer a head start delay may propagate this delay through the daily programme of that aircraft or even the airline’s whole network2.
This end-of-curfew problem couples with flight time limitations to create widespread, recurring delay at the beginning of the day, as the following section discusses.
14 Night Night Curfew Curfew 12
10
8
6
4
2 Planned Departures (30 mins intervals)
0 04:30 05:30 06:30 07:30 08:30 09:30 10:30 11:30 12:30 13:30 14:30 15:30 16:30 17:30 18:30 19:30 20:30 21:30 22:30 Time in UTC
Figure 42 - Planned departures at London-City (EGLC) airport on 30 June 2008. First departures scheduled at opening of airport, last departure scheduled one hour before night ban.
1 Delay Code 89/AM: Restrictions at airport of Departure with or without atfm restrictions. See list of IATA delay codes in Annex C. 2 The propagation of air transport delays in Europe, thesis by Martina Jetzki for the Department of Airport and Air Transportation Research RWTH AACHEN UNIVERSITY, 23 December 2009. A copy of the report can be downloaded from www.eurocontrol.int/coda LCY Departures
40 Planning for Delay: influence of flight scheduling on airline punctuality Trends in Air Traffic l Volume 7 6.3 Operational aspects - Flight Time Limitations (FTL)
Crew flight time limitations, like airport curfews, contribute to a peak of systematic demand (and delays) in the early morning with knock-on effects for the rest of the day.
Flight scheduling involves a complex exercise to streamline all available resources. Crew availability is an essential factor in each flight programme. Every airline will have to make sure that it has enough crew at the right place and at the right time to execute the scheduled programme. It will be impossible to schedule an aircraft to depart from an airport if there is no crew available. Duty and rest time regulations will have an impact on the schedule of some flights.
On July 16, 2008 EU-OPS11 replaced JAR-OPS1. EU-OPS1 regulates the rest and duty times of commercial air crew (EU-FTL) in the EU. Some important concepts of the EU-FTL are:
Flight Duty Period (FDP): A flight duty period is any time during which a person operates in an aircraft as a member of its crew. The FDP starts when the crew member is required by an operator to report for a flight or a series of flights. It finishes at the end of the last flight on which he/she is an operating crew member. The maximum basic daily flight duty period is 13 hours.
Window of Circadian Low (WOCL): The window of circadian low is the period between 02:00h and 05:59h local time (LT). When a FDP starts within the WOCL the maximum basic daily flight duty period will be reduced.
The maximum flight and duty time limitations as set out in EU-Ops1 have an impact on the schedules of most airlines. In order to maximise the operational flexibility of the crew airlines will in most cases not plan a departure earlier than 0600LT. Flights planned to leave prior 0600LT are often short sectors or specific operations (cargo, feeder service etc). The maximum flight duty period will be reduced when the crew report for duty before 0600LT.
The hourly distribution of UK departures on Saturday during summer 2008 shows a sharp increase of traffic as from 0600LT (see Figure 43). There is a high percentage of leisure and charter traffic departing early morning on Saturday from the UK in summer. These flights are often operated to airports around the Mediterranean for which the airlines need to keep the opera- tional flexibility of the crew (i.e. the longest FDP possible).
8%
7%
6%
5%
4%
3%
2%
1%
0% 0:00 2:00 4:00 6:00 8:00 10:00 12:00 14:00 16:00 18:00 20:00 22:00 24:00 Local Time Figure 43 - Planned departures by hour as a percentage of daily departures. Departures on Saturday from the United Kingdom during summer 2008.
1 EU-OPS1 is the transposition into EC law of JAR-OPS 1 as specified by Regulation (EC) No 1899/2006 of the European Parliament and of the Council of 12 December 2006 amending Council Regulation (EEC) NO 3922/91 on the harmonisation of technical requirements and administrative procedures in the field of civil aviation. EU-OPS1 includes some major changes to JAR-OPS Subpart Q, now called EU-FTL
Planning for Delay: influence of flight scheduling on airline punctuality Trends in Air Traffic l Volume 7 41 Figure 44 illustrates the impact of the sharp increase of traffic as from 0600LT (or 0500 UTC). The Average ATFCM Delay per Movement on Departure peaks between 0500UTC and 0600UTC at 5-6 minutes. During the same period more than 25% of all departures suffer an ATFCM delay, again the highest figure observed during the entire day.
The impact of these early morning delays cannot be underestimated. There is a high chance they will spread through the network and affect flights until late in the operational day.1 See Figure 5 on page 6 for the ratio of reactionary to primary delays. For 1 minute of primary delay in 2008 there was 0.83 minute of reactionary delay reported by the airlines.
12 30%
10 ADM 25% PDF 8 20%
6 15% in minutes 4 10%
2 5% Average ATFCM Delay per Movement on Departure per Movement Delay ATFCM Average
0 0% Regulations ATFCM by Delayed of Flights Percentage 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 Time in UTC
Figure 44 - Hourly Average ATFCM Delay per Movement on Departure (ADM) and Percentage of Flights Delayed by ATFCM Regulations (PDF) on flights departing the United Kingdom on Saturday during summer 2008.
1 The propagation of air transport delays in Europe, thesis by Martina Jetzki for the Department of Airport and Air Transportation Research RWTH AACHEN UNIVERSITY, 23 December 2009. A copy of the report can be downloaded from www.eurocontrol.int/coda
42 Planning for Delay: influence of flight scheduling on airline punctuality Trends in Air Traffic l Volume 7 6.4 Taxi-times
An every day experience for many passengers: your flight leaves the gate on time but the aircraft then spends a long time reaching the runway threshold. For some flights the taxi-out time can be even longer than the actual flight time. It’s not only unpleasant for the passengers but also a nightmare for airline schedulers because of the low level of predic- tability of the expected taxi-times.
The start and end of each phase of a flight is always registered. This can be done manually by the Captain, which already gives a good level of accuracy. Automatic recording will generally enhance the accuracy of the data records, but in many cases are expensive (meaning that these systems are not installed at all airports/airlines). Examples of these systems include: aircraft equipped with ACARS (Aircraft Communication and Reporting System), ANSP’s equipped with A-SMGCS (Advanced Surface Movement Guidance and Control System) and airports equipped with a DGS (Docking Guidance System) at the gates.
Variability in taxi-out time can be influenced by:
n Active Runway (wind direction or time of day) n Distance from gate to runway n Weather (remote de-icing and visibility) n Level of congestion (e.g. amount of aircraft lined-up for take-off) n Apron/taxiway lay-out n Aircraft type (aircraft performance) n A-CDM1 variable taxi-times concept n Other factors
Variability in taxi-in time can be influenced by:
n Distance Runway to Gate n Availability of gates n Apron/taxiway lay-out n Level of congestion (e.g. awaiting other aircraft taxiing out of an airport ‘cul-de-sac’) n Weather (visibility) n Other factors
The flight phase can be influenced by the airline (route and speed) whereas the TXI2 and TXO3 can almost never be influenced by the airline. Airlines depend on historical data or predictions when constructing a schedule for a new route or season. Because TXO and TXI can almost never be influenced by the airline it is an accurate and stable indicator for planning purposes if shared with other airlines.
1 A-CDM: Airport Collaberative Decision. More information on www.euro-cdm.org 2 TXI: taxi-in time, the time from landing to on-blocks. 3 TXO: taxi-out, the time from off-blocks to take-off.
Planning for Delay: influence of flight scheduling on airline punctuality Trends in Air Traffic l Volume 7 43 Taxi out
Looking at the variations in taxi-out times at some major European airports + New York-JFK (KJFK) during summer 2008 we can see that none of the listed European airports had more than 1% of flights with a taxi-out in excess of 60 minutes. The median taxi-out varied between 9 minutes at Vienna (LOWW) and 21 minutes at London-Heathrow (EGLL). The median taxi-out at KJFK was 38 minutes, 1% of flights at KJFK had a taxi-out time in excess of 146 minutes (see Figure 45).
60 146
50 TXO 99% TXO Median 40 TXO 1%
30
20
Taxi-Out Time in minutes Time in minutes Taxi-Out 10
0 LOWW LFPO EBBR EKCH LEPA LSZH EDDM LIMC EDDF EDDL EHAM LGAV EGCC LTBA LEMD LFPG EGKK LEBL LIRF EGLL KJFK
Airport of Departure
Figure 45 - Variations of taxi-out times (TXO) at some European airports (+KJFK) during summer 2008.
Taxi in
Looking at the variations in taxi-in times at some major European airports + New York-JFK (KJFK) during summer 2008 we can see that no major European airport had more than 1% of flights with a taxi-in exceeding 30 minutes. Half of the observed European airports had a median taxi-in of 5 minutes. The median taxi-in at Paris-CDG (LFPG) was the highest at 10 minutes, close to the 11 minutes of taxi-in at KJFK (see Figure 46).
60
50 TXI 99% TXI Median 40 TXI 1%
30
20 Taxi-in Time in minutes Time in minutes Taxi-in 10
0 EBBR EDDL EDDM EKCH LEBL LEPA LFPO LGAV LOWW LSZH EDDF LIMC EGCC EGKK EHAM LTBA EGLL LEMD LIRF LFPG KJFK Airport of Arrival
Figure 46 - Variations of taxi-in times (TXI) at some European airports (+KJFK) during summer 2008.
44 Planning for Delay: influence of flight scheduling on airline punctuality Trends in Air Traffic l Volume 7 Typically airlines will examine their own historical data when looking for expected taxi-out times and taxi-in times at the airports where they operate. Datasets based exclusively on own observations are often limited in size. A more accurate figure can be obtained by sharing the data with other airlines (i.e. via the CODA database).
Flights from London-Heathrow (EGLL) to Paris-CDG(LFPG)
Looking at the example of flights operated from London-Heathrow (EGLL) to Paris-CDG (LFPG) (2008) we notice that the variation in the flight phase is mostly influenced by the taxi-out phase. Figure 47 illustrates that 90% of flights need between 38 and 50 minutes from take-off to landing. The average time of the en-route phase is 43 minutes with a standard deviation of 4 minutes.
On flights operated from London-Heathrow (EGLL) to Paris-CDG (LFPG) 90% of flights have a taxi-out time between 12 and 32 minutes and a taxi-in time between 5 and 16 minutes (see Figure 48). The average taxi-out on these flights is 20 minutes with a standard deviation of 7 minutes. The average taxi-in is 11 minutes with a standard deviation of 3 minutes.
90 80
70 En-route 60 50 40 30 Flight time in minutes Flight 20 10 0 % 3% 7% 10% 14% 17% 21% 24% 28% 31% 35% 38% 42% 45% 49% 52% 56% 59% 63% 66% 70% 73% 77% 80% 84% 87% 91% 94% 98%
Figure 47 - 2008 Length of flight time on flights from London-Heathrow to Paris-CDG, as percentage of Actual Block Time.
90 80
70 TXO 60 TXI 50 40 30 Taxi time in minutes Taxi 20 10 0 % 3% 7% 10% 14% 17% 21% 24% 28% 31% 35% 38% 42% 45% 49% 52% 56% 59% 63% 66% 70% 73% 77% 80% 84% 87% 91% 94% 98%
Figure 48 - 2008 Length of taxi times on flights from London-Heathrow to Paris-CDG, as percentage of Actual Block Time.
Planning for Delay: influence of flight scheduling on airline punctuality Trends in Air Traffic l Volume 7 45 Travel time on some transatlantic routes can be strongly influenced by the length of the taxi time. In 2008, flights from New York-JFK to London Heathrow had an average en-route phase of 372 minutes with a standard deviation of 15 minutes. The average taxi-out time at JFK was 38 minutes with a standard deviation of 24 minutes. The taxi-out time exceeded 1 hour on 12% of these flights.
Delays during taxi-out1 are mostly caused by lack of runway capacity at the time of departure. The shortest taxi-out times are therefore observed during periods of low demand, which for most airports will be during the night2. Looking at the taxi-out times at some major European airports we can see that the shortest taxi-out times are during the deep night. The highest average taxi-out times are at the beginning of the operational day. These long taxi-out times have no impact on the departure punctuality of the head-start flights (because the punctuality is based on off-block and not take-off) but may have a reactionary effect on the next flight sectors due to late arrival of the aircraft at the destination airport.
26
24 EDDF EGLL 22 LEMD LFPG LIRF 20 LTBA 18
16
14
Average Taxi-out Time in minutes Taxi-out Average 12
10 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 Actual Time of Departure (UTC)
Figure 49 - 2008: Hourly variations in average Taxi-Out times at some European airports during summer 2008.
26
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22
1 Calculated as the difference between20 the airport declared taxi-out times (often a fixed value) and the actual taxi-out time on the day of operation. 2 Dependant on the Dark: Cargo and Other Night Flights in European Airspace, Eurocontrol Trends in Air Traffic Volume 5, January 2009. 18
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46 12 Planning for Delay: influence of flight scheduling on airline punctuality Trends in Air Traffic l Volume 7 10 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 6.5 Operating speed
In today’s harsh economic climate airlines need to reduce operational costs. Airlines will try to reduce the fixed and variable cost of each flight. Fuel is one of the variable costs that has increased dramatically over recent years.
Airlines around the world are looking at ways to reduce the fuel consumption of each flight. This can be achieved by lowering the weight of the aircraft (the heavier the aircraft the more fuel it needs to carry that weight to the destination). Some airlines reduced the weight of the aircraft by reducing the amount of in-flight magazines carried, carrying less water in their potable water tanks or installing devices to reduce the amount of condensation water in the aircraft. There are many more examples of efforts to reduce weight. Reducing fuel consumption can also be achieved by limiting the use of the APU1, flying the shortest route possible (which may involve longer ATFCM delays), flying at the optimum flight level and flying slower.
The reaction time due to oil price variation may vary according to the airline, as some airlines will buy their jet fuel at current market prices and other airlines will have hedged2 their fuel. Airlines having to buy fuel at current market prices will have to react quicker in a period of increasing fuel prices.
In this section we make a brief examination of the impact of fuel prices on the operational speed of aircraft. Lowering the operational speed of the aircraft will have an effect on the actual flight time. An increase in actual block time that is significant enough and observed over a longer period (at least an entire season) may have an effect on future block times. Operational speed is therefore a planning and operational factor which can influence the daily punctuality and, over time, the entire schedule.
Within the operational limits of the aircraft and airspace, airlines are free to decide at which speed they operate a flight. They can operate a flight at a fixed speed (indicated as a figure relative to the Mach speed) or at a dynamic speed taking variable costs into account.
Jet fuel prices follow the evolution of crude oil prices, although differences by airport are also observed. These differences can be explained by: lack of competition, geographical location of the airport, distance to an oil refinery, traffic volumes, etc.
With the increase in fuel prices (which started in 2004 and peaked in 2007/2008; see Figure 50) airlines saw the share of fuel cost rise to > 30% of their operational costs in 2008. Jet fuel accounted for 14% of operating costs at US$14/barrel Brent in 2003 and for 28% of operating costs in 2007 at US$73/barrel of Brent3.
Trip Cost (Operational Cost per Flight) The cost of a flight is the sum of fixed and variable costs.
Trip Cost (C) = Cf x ∆F + Ct x ∆T + Cc
Cf Cost of fuel per kg ∆F trip fuel Ct time-related cost per minute of flight ∆T trip time Cc Fixed costs independent of time Typically flights will be operated at higher speeds when oil prices are low.
1 APU : Auxiliary Power Unit 2 Fuel Hedging: A fuel hedge contract aims at reducing the risk for an airline of fuel price fluctuations. It contractualy commits airlines to paying a pre-determined price for future jet fuel purchases. Fuel hedging is mostly used when airlines expect price changes by trying to reduce the disruption of confronting future expenses of unknown size. If the price of jet fuel falls and the airline hedged for a higher price, the airline will be forced to pay an above-market rate for jet fuel. 3 Source: www.iata.org/pressroom/facts_figures/fact_sheets/fuel.htm
Planning for Delay: influence of flight scheduling on airline punctuality Trends in Air Traffic l Volume 7 47 Rotterdam Kerosene/Tonne Brent Crude / Barrel 950 100 850
750 80 650
550 60 450
350 40 250
150 20 2000M01 2001M01 2002M01 2003M01 2004M01 2005M01 2006M01 2007M01 2008M01 2009M01 2010M01 2010M11
Figure 50 - Ten-year price evolution Brent Crude Oil (in EUR).
Cost Index
The concept of 950a cost index is to achieve a minimum trip cost by means of a trade-off between100 operating costs per hour and incremental fuel burn. Basically, the cost index is used to take into account the relationship between fuel- and time-related850 costs and requires a Flight Management System (FMS) to be installed in the aircraft. The FMS enables the pilots to fly at the most economic speed depending on the phase of flight, wind conditions, payload etc. The750 cost index can be fixed per flight but can also be changed during the flight80 depending on the operational parameters. 650 Cost Index (CI)= CT/CF 550 Ct Time-related cost per minute of flight 60 Cf Cost450 of fuel per kg The CI is scaled from O to 99 or O to 999 depending on the FMS manufacturer (e.g. Smiths, Sperry, Honeywell). CI units are given in350 kg/min or alternatively as 100 Ib/h. The cost index effectively provides a flexible40 tool to control fuel burn and trip time between these two extremes. The CI for a flight operated by the same carrier can differ from 250 month to month, by aircraft type and even city-pair. When fuel costs are extremely high, flights are operated at a speed which consumes150 least amount of fuel to maximise range. When fuel is relatively cheap, flights are operated at minimum time speed to maximise operational speed. 20 During 2007/2008 when oil prices were very high (up to 140$/barrel Brent Crude Oil) many airlines1 changed from a fixed Mach-speed to a speed based on Cost Index. An analysis of the flight data of carrier XYZ2 shows a reduction
of the average operational2000M01 speed2001M01 (see2002M01 Figure2003M01 51).2004M01 2005M01 2006M01 2007M01 2008M01 2009M01 2010M01 2010M11 Looking more closely at the average speed of flights operated by carrier XYZ we note that they saw a drop of 1.3% during summer 2008 compared with the same period in 2007. A 1.3% drop in speed increased the average flight time by 1.27 minutes in summer 2008 compared to summer 2007. If this increase in actual flight time is observed over a longer period, carriers may decide to update the scheduled block time accordingly and avoid an increase in reactionary delays.
1 www.guardian.co.uk/environment/2008/jun/28/travelandtransport.oil 2 Carrier XYZ has been anonymised for reasons of confidentiality, however it is known that the airline reduced the operational speed of its fleet during summer 2008 due to high oil prices.
48 Planning for Delay: influence of flight scheduling on airline punctuality Trends in Air Traffic l Volume 7 400
395
390
Average Speed (Kts) Average 385
380 Jul-07 Jul-08 Oct-07 Oct-08 Jan-07 Jan-08 Jun-07 Jun-08 Apr-07 Apr-08 Feb-07 Feb-08 Dec-07 Dec-08 Sep-07 Sep-08 Nov-07 Nov-08 Mar-07 Mar-08 Aug-07 Aug-08 May-07 May-08
Figure 51 - Average speed of flights operated by carrier XYZ. (Network wide)
Looking at a specific airport pair operated by carrier XYZ we can see that the average flight time between Airport A and Airport B increased from 139 minutes to 145 minutes (+ 4.3%) between summer 2007 and summer 2008. This increase of actual flight time was caused by a decrease of the average speed from 409 Kts to 404 Kts (- 1.3%). Another driver for the increase in actual flight time was the growth in the actual distance flown (from 947NM in 2007 to 973NM in 2008). The change in actual distance flown caused a 2.7% increase in flight time (see Figure 52).
1000 150
950 140 Distance (NM) Flight Time in minutes Flight
900 130 Jul-08 Jul-07 Oct-08 Oct-07 Jan-08 Jan-07 Jun-08 Jun-07 Apr-08 Apr-07 Feb-08 Feb-07 Dec-08 Dec-07 Sep-08 Sep-07 Nov-08 Nov-07 Mar-08 Mar-07 Aug-08 Aug-07 May-08 May-07
Figure 52 - Average flight time and distance flown on city pair A-B by carrier XYZ.
High fuel prices, as observed during 2007/2008, do not seem to have had an effect on the scheduled block times of the observed carrier in the long run if the airline continues to operate the same aircraft type on the same route. Switching from a jet aircraft to a more fuel efficient but slower Turboprop aircraft will, of course, have an effect on the block time. Changes in actual time which are < 5 minutes will not have an effect on the scheduled block time in many cases. Small changes in actual block time in combination with other factors (longer taxi-out times, etc.) could however trigger a review of the scheduled block times.
Planning for Delay: influence of flight scheduling on airline punctuality Trends in Air Traffic l Volume 7 49 6.6 Wind
Anybody who has travelled on a long-haul flight will have noticed the effect of wind on the travel time. Whilst head- winds will reduce the speed of the aircraft relative to the earth, tailwinds have a more pleasant effect with an increased speed and thus shorter travel time. Changes in seasonal winds aloft may have an important influence on the schedules.
When building a schedule for new routes airlines will typically simulate a series of flights to determine a feasible block time using specific software to calculate the flight plans. The airline will run a series of flight plans based on the historical wind records on these routes. Schedules are built on the expected flight time on CDR11 routes. (Note that historical data will also include CDR2 & 3 routes, if made available to the airline). For the purpose of this analysis the change in routes was not examined, the average route length in nautical miles changed approximately 1% depending on the season.
Wind has almost no effect on the schedule for short-haul flights. Long-haul flights, however, can see strong seasonal variations in flight time due to changes in wind direction and speed at certain flight levels. A typical example is the jet stream over the Atlantic Ocean which generates strong tailwinds for eastbound traffic and headwinds for westbound traffic.
Polar Jet Stream
Polar Front Subtropical Jet Stream
Intertropical Convergence zone
Polar Front
Figure 53 - Polar and subtropical jet streams2
1 CDR Routes: A non-permanent Air Traffic Services (ATS) route or portion thereof which can be planned and used under specified conditions. According to their foreseen availability, flight planning possibilities and the expected level of activity of the possible associated Temporary Segregated Areas (TSA), Conditional Route (CDRs) can be divided into the following categories: Category One: Permanently Plannable CDR, Category Two: Non-Permanently Plannable CDR, Category Three: Not Plannable CDR. 2 Pidwirny, M. Jones, S. (2010) Physical Geography available at: http://www.physicalgeography.net
50 Planning for Delay: influence of flight scheduling on airline punctuality Trends in Air Traffic l Volume 7 Transatlantic flights Looking at the en-route times1 (time between take-off and landing) on a typical transatlantic route between London-Heathrow (EGLL) and New York-JFK (KJFK) there is an impressive difference between the average flight time on westbound flights compared with traffic flying eastbound. The monthly average flight time on westbound flights between EGLL and KJFK can be up to 460 minutes with eastbound flights being as low as 365 minutes.
London-Heathrow to New York-JFK Seasonal variations in flight times on the EGLL-KJFK sector are bigger compared to the return flight. The average monthly flight time varies between 400 minutes in summer and 450 minutes in winter. The magnitude of these variations has an effect on scheduled block times, which are longer in winter.
New York-JFK to London-Heathrow London-Heathrow to New York-JFK Seasonal variations on the JFK-LHR sector are different compared to flights flying EGLL-KJFK. The average flight time varies between 365 minutes and 385 minutes. This difference in flight time 480is insufficient to change the scheduled block times, which480 is stable at an average around 420 minutes. 460 460
440 Increased scheduled block times during the winter months on flights operated from EGLL to KJFK cannot completely compen440 - sate for the increase in actual flight time. As shown in Figure 56, the BTO420 and DDI-F reach their highest values during the winter420 months when flight times are the longest. Flights operated in winter will have a higher risk of arrival delays compared to flights 400 operated in summer. 400 380 380 Average Flighttime (En-route) in minutes (En-route) Flighttime Average Flights operated eastbound show smaller seasonal variance in the Scheduled Blocktime in minutes Average flight time (see Figure 54 & Figure 55), but this still has an 360 360 influence on the BTO and DDI-F as shown in Figure 57. A small increase in flight time in May 2008 means that the BTO jumps Jul-07 Jul-08 Oct-07 Oct-08 Jan-07 Jan-08 Jun-07 Jun-08 Apr-07 Apr-08 Feb-07 Feb-08 Dec-07 Dec-08 Sep-07 Sep-08 Nov-07 Nov-08 Mar-07 Mar-08 Aug-07 Aug-08 to 61% and the DDI-F to +10 minutes. May-07 May-08
London-Heathrow to New York-JFK New York-JFK to London-Heathrow
480 480 480 480
460 460 460 460
440 440 440 440
420 420 420 420
400 400 400 400
380 380 380 380 Average Flighttime (En-route) in minutes (En-route) Flighttime Average Average Flighttime (En-route) in minutes (En-route) Flighttime Average Average Scheduled Blocktime in minutes Average Average Scheduled Blocktime in minutes Average 360 360 360 360 Jul-08 Jul-07 Jul-08 Jul-07 Oct-08 Oct-07 Jan-08 Jan-07 Oct-08 Oct-07 Jan-08 Jan-07 Jun-08 Jun-07 Apr-08 Apr-07 Feb-08 Feb-07 Jun-08 Jun-07 Apr-08 Apr-07 Dec-08 Dec-07 Feb-08 Feb-07 Sep-08 Sep-07 Dec-08 Dec-07 Sep-08 Sep-07 Nov-08 Nov-07 Mar-08 Mar-07 Nov-08 Nov-07 Aug-08 Aug-07 Mar-08 Mar-07 Aug-08 Aug-07 May-08 May-07 May-08 May-07
Figure 54 & 55 - Flight times and Scheduled times influenced by prevailing winds aloft on Transatlantic Flights. New York-JFK to London-Heathrow
480 480
1 En-route460 times are not influenced by the length of the departure delay460 (if any delay occured) or by taxi-times.
440 440
420 420
400 400
380 380
Planning for Delay: influence of flight scheduling on airline punctuality Trends in minutes (En-route) Flighttime Average in Air Traffic l Volume 7 51 Average Scheduled Blocktime in minutes Average 360 360 Jul-07 Jul-08 Oct-07 Oct-08 Jan-08 Jan-07 Jun-07 Jun-08 Apr-07 Apr-08 Feb-08 Feb-07 Dec-07 Dec-08 Sep-07 Sep-08 Nov-07 Nov-08 Mar-08 Mar-07 Aug-07 Aug-08 May-07 May-08 London-Heathrow to New York-JFK
80% 20 70% 15 60% 10 50% 5 40%
BTO 0 DDI-F 30% -5 20% -10 10% -15 0% -20 Jul-07 Jul-08 Oct-07 Oct-08 Jan-07 Jan-08 Jun-07 Jun-08 Apr-07 Apr-08 Feb-07 Feb-08 Dec-07 Dec-08 Sep-07 Sep-08 Nov-07 Nov-08 Mar-07 Mar-08 Aug-07 Aug-08 May-07 May-08
London-Heathrow to New York-JFK New York-JFK to London-Heathrow
80% 20 80% 20 70% 15 70% 15 60% 10 60% 10 50% 5 50% 5 40% 40% BTO
BTO 0 0 DDI-F DDI-F 30% -5 30% -5 London-Heathrow to Singapore 20% -10 20% -10 10% 10% -15 900 900-15 0% -20 0% -20
850 Jul-07 Jul-08
Jul-07 Jul-08 850 Oct-07 Oct-08 Jan-07 Jan-08 Jun-07 Jun-08 Apr-07 Apr-08 Oct-07 Oct-08 Jan-07 Jan-08 Feb-07 Feb-08 Dec-07 Dec-08 Jun-07 Jun-08 Sep-07 Sep-08 Apr-07 Apr-08 Feb-07 Feb-08 Nov-07 Nov-08 Dec-07 Dec-08 Sep-07 Sep-08 Mar-07 Mar-08 Aug-07 Aug-08 Nov-07 Nov-08 Mar-07 Mar-08 Aug-07 Aug-08 May-07 May-08 May-07 May-08
Figure 56 & 57 - Monthly BTO and DDI-F on Transatlantic Flights. 800 800
New York-JFK to London-Heathrow Flights to SE-Asia 750 750
Similarly80% to the transatlantic flights, flight times of flights to SE-Asia are subject to variations caused by the seasonal change in winds
20 in minutes (En-route) Flighttime Average Average Scheduled Blocktime in minutes Average aloft. Flights operated between London/LHR and Singapore show little700 seasonal variation in the flight time on eastbound flights. 70% 15 700 Flights operated from Singapore to London/LHR take longer during the winter months compared to the summer months. The 60%
10 Jul-07 Jul-08 Oct-07 Oct-08 Jan-07 Jan-08 Jun-07 Jun-08 Apr-07 Apr-08 Feb-07 Feb-08 Dec-07 Dec-08 Sep-07 Sep-08 Nov-07 Nov-08 Mar-07 Mar-08 Aug-07 Aug-08 average flight time on flights from Singapore to LHR can be up to 60 minutes longerMay-07 in winter compared to theMay-08 summer months. Scheduled50% Block times therefore follow the seasonal change5 in flight times (see Figure 59). 40% BTO 0 DDI-F 30% London-Heathrow to Singapore -5 Singapore to London-Heathrow 20% -10 London-Heathrow to Singapore
90010% 900-15 900 900 80% 0% -20 25 70% 20 850 850 850 850 Jul-07 Jul-08 Oct-07 Oct-08 Jan-07 Jan-08 Jun-07 Jun-08 Apr-07 Apr-08 Feb-07 Feb-08 Dec-07 Dec-08 Sep-07 Sep-08 Nov-07 Nov-08 Mar-07 Mar-08 Aug-07 Aug-08 May-07 May-08 60% 15
50% 10 800 800 800 8005 40% BTO
0 DDI-F 30% 750 750 750 750-5 20% -10 Average Flighttime (En-route) in minutes (En-route) Flighttime Average Average Flighttime (En-route) in minutes (En-route) Flighttime Average Average Scheduled Blocktime in minutes Average
Average Scheduled Blocktime in minutes Average 10% 700 700 700 700-15 0% -20 Jul-07 Jul-08 Jul-07 Jul-08 Oct-07 Oct-08 Jan-07 Jan-08 Jun-07 Jun-08 Apr-07 Apr-08 Feb-07 Feb-08 Dec-07 Dec-08 Sep-07 Sep-08 Oct-07 Oct-08 Jan-07 Jan-08 Nov-07 Nov-08 Jun-07 Jun-08 Apr-07 Apr-08 Mar-07 Mar-08 Feb-07 Feb-08 Aug-07 Aug-08 Dec-07 Dec-08 Sep-07 Sep-08 May-07 May-08 Nov-07 Nov-08 Mar-07 Mar-08 Aug-07 Aug-08 May-07 May-08 Jul-07 Jul-08 Oct-07 Oct-08 Jan-07 Jan-08 Jun-07 Jun-08 Apr-07 Apr-08 Feb-07 Feb-08 Dec-07 Dec-08 Sep-07 Sep-08 Nov-07 Nov-08 Mar-07 Mar-08 Aug-07 Aug-08 Figure 58 & 59 - Flight times and Scheduled times influenced by May-07 prevailing winds aloft. May-08
Singapore to London-Heathrow London-Heathrow to Singapore Singapore to London-Heathrow 900 900 80% 25 80% 25 70% 70% 20 850 85020 60% 15 60% 15
50% 10 50% 10 800 800 5 5 40% 40% BTO BTO DDI-F 0 DDI-F 0 75030% 30% 750-5 -5 20% 20% -10 -10 in minutes (En-route) Flighttime Average Average Scheduled Blocktime in minutes Average 70010% 700-15 10% -15 0% -20 0% -20 Jul-07 Jul-08 Oct-07 Oct-08 Jan-07 Jan-08 Jun-07 Jun-08 Apr-07 Apr-08 Feb-07 Feb-08 Dec-07 Dec-08 Sep-07 Sep-08 Nov-07 Nov-08 Mar-07 Mar-08 Aug-07 Aug-08 May-07 May-08 Jul-07 Jul-08 Jul-07 Jul-08 Oct-07 Oct-08 Jan-07 Jan-08 Jun-07 Jun-08 Apr-07 Apr-08 Oct-07 Oct-08 Jan-07 Jan-08 Feb-07 Feb-08 Dec-07 Dec-08 Jun-07 Jun-08 Sep-07 Sep-08 Apr-07 Apr-08 Feb-07 Feb-08 Nov-07 Nov-08 Dec-07 Dec-08 Sep-07 Sep-08 Mar-07 Mar-08 Aug-07 Aug-08 Nov-07 Nov-08 Mar-07 Mar-08 Aug-07 Aug-08 May-07 May-08 May-07 May-08
Figure 60 & 61 - Monthly BTO and DDI-F on flights to/from SE Asia.
Singapore to London-Heathrow
52 Planning for Delay: influence of flight scheduling on airline punctuality Trends in Air Traffic l Volume 7 80% 25 70% 20
60% 15
50% 10 5 40% BTO
0 DDI-F 30% -5 20% -10 10% -15 0% -20 Jul-07 Jul-08 Oct-07 Oct-08 Jan-07 Jan-08 Jun-07 Jun-08 Apr-07 Apr-08 Feb-07 Feb-08 Dec-07 Dec-08 Sep-07 Sep-08 Nov-07 Nov-08 Mar-07 Mar-08 Aug-07 Aug-08 May-07 May-08 6.7 Time of Operation
The scheduled time of departure and scheduled time of arrival may be influenced by legal or operational limitations (see sections 6.2 and 6.3). Commercial reasons of course, will have the biggest influence on the setting of scheduled times.
Traffic demand is not spread equally in time and shows strong seasonal/monthly/daily or even hourly variations. Some of these changes in traffic demand are caused by operational constraints (e.g. crew duty times, airport opening hours etc). Others are caused by a large increase in passenger demand such as summer traffic to leisure destinations around the Mediterranean in summer, ski traffic in winter or big sport events (Olympic Games, World Football Championship etc.). Traffic flow overloads are managed tactically by the CFMU who will apply flow restrictions and cause ATFCM delays for the airlines. High peaks in demand may also lead to an overload at the airport and cause airport related delays like ramp congestion, late closure of check-in etc.
Traffic at some smaller leisure destinations is concentrated during specific days of the week. Tourists arrive and depart on specific days of the week with hardly any leisure or charter flights on other days of the week.
As an example, Figure 62 illustrates the total arrivals by day of the week at Kerkira/Corfu (LGKR). Saturday is the busiest day of the week when a quarter of the weekly traffic arrives at the airport: an even spread of traffic would mean that 1/7th or 14% of the weekly traffic arrives each day, see grey area on graph. The average delay per movement on departure for all causes of delay (ADMD) for flights departing LGKR also peaks on Saturday at 28.22 minutes per movement.
30% 30
Share of weekly trac 25% ADMD 25
20% 20
15% 15
10% 10 Share of weekly trac Share of weekly
5% (ADMD) causes‘’ ‘’all Departure
5 on per Movement Delay Average
0% 0 Mon Tue Wed Thu Fri Sat Sun
Figure 62 - Overview of daily traffic share and Average Delay per Movement on Departure “All Causes” at leisure destination Kerkira/Corfu (LGKR) during June to August 2008. Non-coordinated during winter, coordinated during summer.
Planning for Delay: influence of flight scheduling on airline punctuality Trends in Air Traffic l Volume 7 53 Flights to Hurghada (HRG-HEGN) peak on Thursday when almost 20% of the weekly flights to Europe depart (see Figure 63). Wednesday is the quietest day of the week when only 7% of weekly flights depart. The impact of the higher volume of traffic on Thursday can be seen by the sharp increase of ATFCM delays. The average ATFCM delay per movement jumps from 2.77 minutes on Wednesday to 10.83 minutes on Thursday: an increase of 300%.
25% 25
Share of weekly trac 20% ADM-ATFCM 20
15% 15
10% 10 on Departure Share of weekly trac Share of weekly 5% 5 Average ATFCM Delay per Movement per Movement Delay ATFCM Average 0% 0 Mon Tue Wed Thu Fri Sat Sun
Figure 63 - Overview of daily traffic share and Average ATFCM Delay per Movement on flights departing Hurghada (HEGN) in 2008.
54 Planning for Delay: influence of flight scheduling on airline punctuality Trends in Air Traffic l Volume 7 7. LEAVING ON-TIME OR ARRIVING ON-TIME?
Although passengers will appreciate the fact that their flight leaves on-time, it is of even more importance that their flight consequently arrives on-time. Apart from the price of the ticket the scheduled time of arrival will be one of the most important reasons for many passengers booking a specific flight.
Aviation, like any other industry, uses specific KPIs1 to measure and monitor the performance of airlines. Investors will probably look for financial figures, aviation authorities might have more interest in the safety record. Passengers on the other hand are very often interested in the operational performance of an airline. Like any other KPI used across an industry it is essential that everybody uses the same methodology.
There are a vast number of operational performance indicators used by airlines:
n RPKs2 n Load factor n Dispatch reliability of aircraft n Denied boarding of passengers due to over sales n Rate of diversions n Rate of cancelled flights n Flight Punctuality n Other indicators
Flight punctuality, or On-Time Performance, is used by airlines, ANSPs and airports to monitor the operational performance of their services. These punctuality figures are specific to each service provider (e.g. a flight might be delayed on departure for the airline due to handling problems but the same flight might appear as on-time for the ANSP because no ATC slot was given).
Departure or Arrival punctuality? Traditionally there has been a focus on the measurement of departure punctuality. In Europe, delay codes are used to identify departure delays and not to identify arrival delays. Arrival punctuality on the other hand is a very important indicator for the stability of the airline’s network. On-time arrivals are of greater importance for the stability of the airline’s flight operations than an on-time departure.
On-time arrivals mean that passengers can make their connections, that aircraft can be prepared in time for the next flight, that crew have sufficient time to change aircraft in case they are operating multiple-sectors, and it avoids late minute gate changes with possible lost passengers etc. Airlines will still focus on the departure phase because an on-time departure is the best guarantee for an on-time arrival. Strong headwinds, very long taxi-times, unrealistic block times, and holdings etc can still cause arrival delays in case of an on-time departure.
Looking at a schedule as a commitment from an airline to their client, delays on the first stage of a multiple leg journey will be (almost) completely neutralised if the passenger was able to catch his onward connection (given that the following or later legs of the journey were operated on-time of course).
1 KPI: Key Performance Indicator 2 RPK: The RPK of an airline is the the sum of the products obtained by multiplying the number of revenue passengers carried on each flight stage by the stage distance or it is the total number of kilometres travelled by all passengers.
Planning for Delay: influence of flight scheduling on airline punctuality Trends in Air Traffic l Volume 7 55 Percentage of Flights Delayed In 2008, 15.2% of flights departed 5 minutes or more before their planned time and 60% of flights departed within 5 minutes of the planned time. Of all delayed flights on departure 21.4% were delayed by more than 15 minutes. On the other hand, 21.6% of flights arrived > 15 minutes after the STA1.
PDFD > 15 mins PDFA > 15 mins 25% 25%
PDFD > 15 mins PDFA > 15 mins 20%25% 20%25%
15%20% 15%20% 2004 2005 2006 2007 2008
Figure 64 - Percentage of Delayed Flights on Departure > 15 mins of STD compared with Percentage of Delayed Flights on Arrival > 15 mins of STA.
Average Delay per Movement Flights leaving or arriving ahead of scheduleADMD are considered to be delay neutralADMA for the calculation of average delay minutes. 15%13 1315% The average delay per movement is the total2004 generated2005 delay2006 minutes2007 divided2008 by all movements.
For the first time in the last five years, there was a drop in the average delay per movement. In 2008, the Average Delay per Movement was 12.6 minutes, a decrease12 of 2.1% on 2007. 12
ADMD ADMA 1311 1311
1210 1210
119 119 2004 2005 2006 2007 2008
10 10
ADDD > 15 mins ADDA > 15 mins 509 950 2004 2005 2006 2007 2008
Figure 65 - Average Delay per Movement on Departure compared with Average Delay per Movement on Arrival.
1 CODA Delay Digest - Annual 2008, 03 March 2009. www.eurocontrol.int/coda ADDD > 15 mins ADDA > 15 mins 50 50 56 45 Planning for Delay: influence of flight scheduling on airline45 punctuality Trends in Air Traffic l Volume 7
4045 4045 2004 2005 2006 2007 2008
40 40 2004 2005 2006 2007 2008 PDFD > 15 mins PDFA > 15 mins 25% 25%
20% 20%
15% 15% 2004 2005 2006 2007 2008
ADMD ADMA 13 13
12 12
11 11
10 10
9 9 Average Delay per Movement for Flights Delayed2004 2005> 15 mins2006 2007 2008 Unlike the drop in Average Delay per Movement and Percentage of Delayed Flights, there was an increase in the Average Delay per Delayed Flight in 2008. The 21.4% of flight that experienced a departure delay > 15 minutes had an average departure delay of 48 minutes. This is an increase of one minute compared with 2007.
ADDD > 15 mins ADDA > 15 mins 50 50
45 45
40 40 2004 2005 2006 2007 2008
Figure 66 - Average Delay per Delayed Departure > 15 mins and Average Delay per Delayed Arrival > 15 mins.
Departure Delay Causes An analysis of the delay causes, grouped by IATA delay code1, indicates an increase in the reactionary/primary delay ratio over recent years. In 2008, the reactionary/primary delay ratio was 0.83. This means that for each minute of primary delay there was 0.83 minute of reactionary delay. Figure 5 on page 6 shows that the reactionary/primary delay ratio has significantly increased from 2003 to 20082. In 2003 the ratio was 0.23. This evolution indicates a loss in delay recovery for airlines and calls for further investigation.3
1 See annex C for a detailed list of the IATA delay codes and annex D for CODA delaygroups 2 In 2009 the ratio dropped and was again at 2007 levels. See PRR2009, Performance Review Report 2009, 06 May2010, §4.6.5. 3 The propagation of air transport delays in Europe, thesis by Martina Jetzki for the Department of Airport and Air Transportation Research RWTH AACHEN UNIVERSITY, 23 December 2009. A copy of the report can be downloaded from www.eurocontrol.int/coda
Planning for Delay: influence of flight scheduling on airline punctuality Trends in Air Traffic l Volume 7 57 8. DELAY MONITORING SYSTEMS & USE OF CODA ON-LINE APPLICATIONS
‘‘If you cannot measure it, you cannot improve it.’’ – William Thomson (Lord Kelvin)
Measuring their operational performance is an essential aspect of every airline’s daily business. Measuring alone will not bring the expected improvements of course. Airlines want to monitor and compare their current performance with their own historical performance and use competitor’s data as a benchmark. The EUROCONTROL Central Office for Delay Analysis (CODA) collects individual airlines data, integrates it with CFMU data and makes it available to the airline community for performance analysis.
Airlines use their internal systems and procedures to collect data and monitor their (operational) performance. Data can be logged automatically (e.g. ACARS, automated crew sign-in etc)1 or manually (e.g. Captain’s logbook, technical logbook etc). Information gathered with these systems is stored in purpose built data warehouses or within the flight operations control system. The data collection, validation, storage and analysis can be very expensive and unless external data is acquired the available data is limited to that of the airline itself.
More and more airlines realise that sharing (some) information is a win-win situation. It avoids having to buy additional data on the market and it increases the scope of the own database.
The Central Office for Delay Analysis (CODA) has been collecting and sharing data since 1997. At first this was mainly focused on CFMU data. From 2002 onwards the database has been enriched with data provided directly by the airlines. CODA collects a range of data items direct from the airlines2.
Each file that an airline sends to CODA will have to pass a Quality Check before being loaded in the PRISME3 database. Flights are first linked with CFMU ETFMS4 data. Once this is done a series of quality filters are applied. Flights passing these filters are automatically loaded into the database, while flights that were blocked by one or more of the filters are corrected manually before entry.
Airlines providing data to CODA have full access to their own data set (which is now linked to CFMU data). Airlines are also able to access the shared database. There is unlimited access with a limitation on the level of granularity for some of the reports.
1 ACARS: Automatic Communicaton Adressing and Reporting System 2 See annex B: list of data items collected from the airlines 3 PRISME: Pan-European Repository of Information Suporting the Management of EATM (European Air Traffic Management) 4 ETFMS: Enhanced Tactical Flow Management System
58 Planning for Delay: influence of flight scheduling on airline punctuality Trends in Air Traffic l Volume 7 The CODA portal offers a range of on-line products to different stakeholders on both macro and detailed levels.
1. Public
n Monthly FLAD1, published three weeks after the end of the month n Monthly Digest, full report published six weeks after the end of the month n Seasonal Digest covering the Summer season, published six weeks after the end of the period n yearly report, covering a full year, published six-eight weeks after the end of the period
2. Other Industry Partners & Airports
n An Analysis Tool where the level of granularity of the output restricts the identification of the individual data supplier
3. Airlines providing data
n CORE (see insert) n Analysis Tool (see insert) p Overview of Data Providers p Selection (detailed analysis) p General Statistics p Timeline Significant events p ACARS Quality Log p Airport map tool
Macro analysis Regular CODA publications report on aggregated delay indicators. These monthly/ seasonal/ yearly digests have a high-level approach and use the data supplied by airlines for reports on delays “All Causes”. Delays “All Causes” include Primary and Reactionary delays. Primary delays occur during the ground phase of the flight that was delayed. Reactionary delays on the other hand are delays where the initial reason for the delay occurred somewhere else.
The share of primary departure delays (as from one minute delay) caused by airlines dropped by 2% in 2008 compared with 2007. The share of Airport, Weather, Security and Miscellaneous delays was little changed (see figure 67). ATFCM2 En-Route delays increased by 3% in 2008 and represents 13% of all primary departure delays. When demand exceeds the en-route capacity restrictions will protect the system from overloads and delays are generated. A contributing factor in 2008 was the reduced flexibility of airlines to accept (proposed) longer re-routings to avoid delays. In a number of cases airlines preferred to accept a delay and fly the shorter route instead of flying a slightly longer route with fewer en-route delays. High fuel prices reduced the operational flexibility of many airlines.
1 FLAD: First Look at Delays. A preliminary report on the delays of the previous month. 2 ATFCM: Air Traffic Flow and Capacity Management
Planning for Delay: influence of flight scheduling on airline punctuality Trends in Air Traffic l Volume 7 59 (Based on the All Causes Total Delay - as from 1 minute) Source: EUROCONTROL CODA
Weather 10%
13% 54%
Total ATFCM Delay Primary 28% Departure Delay Causes for 2008
Airport 17%
3% 3%
Weather 10%
13% 56%
Total ATFCM Delay 24% Primary Departure Delay Causes Airline for 2007 Miscellaneous Airport Security 17% Airport ATFCM Airport En-route ATFCM Weather Weather 4% 3%
Figure 67 - Primary departure delay causes 2008 vs 2007.
Detailed analysis The CODA reports at the detailed level are only available via the secured pages of the CODA portal. These detailed reports are made available to airlines and specific industry partners (like airports, ANSP’s, CAA’s etc.). The level of granularity of the output varies by user. Airlines have full access to their own data but can only view aggregated data on their competitors.
60 Planning for Delay: influence of flight scheduling on airline punctuality Trends in Air Traffic l Volume 7 CORE The CORE (CODA REport) offers a quick and easy comparison of operational charts and tables between the user’s own airline, a virtual airline and all the airlines in Europe. The majority of the charts are based on CODA data. Other charts are based on data supplied by the CFMU.
Each CORE is e-mailed to the user in PDF format. The column-based lay-out of the CORE enables the user to compare some pre-defined KPIs of their own airline with two other groups of airlines. A logo on top of each column indicates the data source and the filtering criteria. The results are displayed underneath.
First column:
n Individual Airline data, the logo of the data provider is displayed. This column displays the results based on the data provider’s data set;
n Source: Individual Airline’s data;
n Filter criteria:
p Date Range, Selection of specific company call signs, Aircraft Type, Flight Type, Sector Length.
Second column:
n virtual Airline based on actual data received from participating airlines (> 120 airlines) taking the selected criteria into account. If no selection criteria are defined it is identical to the EUROCONTROL column;
n Source: All Airlines providing data to CODA;
n Filter criteria:
p Date range, Aircraft Type, Flight Type, Sector Length, Company Size by annual operated flights in Europe.
Third column:
n EUROCONTROL column, this column groups the data received from all participating Airlines (> 120 airlines). Apart from the date range, the selection criteria are not taken into account. In case of CFMU data it groups all airlines operating in Europe;
n Source: Individual Airline’s data;
n Filter criteria:
p Date Range.
Planning for Delay: influence of flight scheduling on airline punctuality Trends in Air Traffic l Volume 7 61 Figure 68 - CODA – Airline application. Access to CORE and Analysis Tool.
Figure 69 - Front page CORE (CODA Report).
62 Planning for Delay: influence of flight scheduling on airline punctuality Trends in Air Traffic l Volume 7 Analysis Tool Applications
n Analysis Tool – Data Providers The overview of current data providers.
n Analysis Tool – Selection The selection screen in the CODA Analysis Tool allows detailed analysis of the airline’s performance based on its own data or based on the CFMU database.
n Analysis Tool – General Statistics The General Statistics gives an indication of the data loading process. A dynamic map allows the user to visualise the CODA coverage of IFR flights by European state.
n Analysis Tool – Timeline Significant Events The timeline of significant events provides a quick overview of events that had an effect on the European network.
n Analysis Tool – ACARS Quality Log The Acars Quality Log allows airlines to monitor the CODA QC and corrections done on their flights.
n Analysis Tool – Airport Map Tool The Airport Map Tool allows airlines to filter the delays by airport and ATFM/All Causes of delay and visua- lise it on a map.
Figure 70 - Screenshot CODA On-Line Analysis Tool.
Planning for Delay: influence of flight scheduling on airline punctuality Trends in Air Traffic l Volume 7 63 Figure 71 - Screenshot CODA On-Line Analysis Tool – General Statistics – map tool.
Figure 72 - Screenshot CODA On-Line Analysis Tool – Significant Events.
64 Planning for Delay: influence of flight scheduling on airline punctuality Trends in Air Traffic l Volume 7 Figure 73 - Screenshot CODA On-Line Analysis Tool – Airport Map tool.
Planning for Delay: influence of flight scheduling on airline punctuality Trends in Air Traffic l Volume 7 65
A. CODA data partners
Planning for Delay: influence of flight scheduling on airline punctuality Trends in Air Traffic l Volume 7 67 68 Planning for Delay: influence of flight scheduling on airline punctuality Trends in Air Traffic l Volume 7 Planning for Delay: influence of flight scheduling on airline punctuality Trends in Air Traffic l Volume 7 69 B. Data items collected by CODA1
Cy ICAO 3-letter code of the company that flies the aircraft CallSign IACO 3-letter flight number prefix followed by the flight number (no blanks) ComFltNbr The commercial flight number (as given to airports for passenger info displays) AcReg 5 characters (no hyphen) Dep ICAO 4-letter code of the departure station (the IATA 3-letter code can also be accepted) Dst ICAO 4-letter code of the destination station (the IATA 3-letter code can also be accepted) Std Standard Time of Departure according to the schedules including the date Sta Standard Time of Arrival according to the schedules including the date Eet (FP) Estimated Flight time in minutes according to the flight plan Out Actual Time of Departure from the gate including the date Off Actual Time of Take-off including the date On Actual Time of Landing including the date In Actual Time of Arrival at the gate including the date Dl1 First delay cause in IATA 2 digit code Time1 First delay cause duration in minutes Dly2 Second delay cause in IATA 2 digit code Time2 Second delay cause duration in minutes Dly3 Third delay cause in IATA 2 digit code Time3 Third delay cause duration in minutes Dly4 Fourth delay cause in IATA 2 digit code Time4 Fourth delay cause duration in minutes Dly5 Fifth delay cause in IATA 2 digit code Time5 Fifth delay cause duration in minutes RD from Flt If there is a reactionary delay, give the call sign of the flight having directly caused the reactionary delay STXO Standard Outbound Taxi Time in minutes STXI Standard Inbound Taxi Time in minutes ServType Service Type (see IATA SSIM appendix C) (1 character) FltType Flight Type («S» for Scheduled or «N» for Non-scheduled (Charter)) QC Quality Control («A» for ACARS, «M» for Manual or «C» for Combination or both)
1 Minimum required data items for data analyis marked in Italic
70 Planning for Delay: influence of flight scheduling on airline punctuality Trends in Air Traffic l Volume 7 C. IATA Delay codes list
Others
00-05 AIRLINE INTERNAL CODES 06 (OA) NO GATE/STAND AVAILABILITY DUE TO OWN AIRLINE ACTIVITY 09 (SG) SCHEDULED GROUND TIME LESS THAN DECLARED MINIMUM GROUND TIME
Passenger and Baggage
11 (PD) LATE CHECK-IN, acceptance after deadline 12 (PL) LATE CHECK-IN, congestions in check-in area 13 (PE) CHECK-IN ERROR, passenger and baggage 14 (PO) OVERSALES, booking errors 15 (PH) BOARDING, discrepancies and paging, missing checked-in passenger 16 (PS) COMMERCIAL PUBLICITY/PASSENGER CONVENIENCE, VIP, press, ground meals and missing personal items 17 (PC) CATERING ORDER, late or incorrect order given to supplier 18 (PB) BAGGAGE PROCESSING, sorting etc. 19 (PW) Boarding/Deboarding of passengers with reduced mobility1
Cargo and Mail
21 (CD) DOCUMENTATION, errors etc. 22 (CP) LATE POSITIONING 23 (CC) LATE ACCEPTANCE 24 (CI) INADEQUATE PACKING 25 (CO) OVERSALES, booking errors 26 (CU) LATE PREPARATION IN WAREHOUSE 27 (CE) DOCUMENTATION, PACKING etc (Mail Only) 28 (CL) LATE POSITIONING (Mail Only) 29 (CA) LATE ACCEPTANCE (Mail Only)
Aircraft and Ramp Handling
31 (GD) AIRCRAFT DOCUMENTATION LATE/INACCURATE, weight and balance, general declaration, pax manifest, etc. 32 (GL) LOADING/UNLOADING, bulky, special load, cabin load, lack of loading staff 33 (GE) LOADING EQUIPMENT, lack of or breakdown, e.g. container pallet loader, lack of staff 34 (GS) SERVICING EQUIPMENT, lack of or breakdown, lack of staff, e.g. steps 35 (GC) AIRCRAFT CLEANING 36 (GF) FUELLING/DEFUELLING, fuel supplier 37 (GB) CATERING, late delivery or loading 38 (GU) ULD, lack of or serviceability 39 (GT) TECHNICAL EQUIPMENT, lack of or breakdown, lack of staff, e.g. pushback
1 will appear in AHM730 in 2011
Planning for Delay: influence of flight scheduling on airline punctuality Trends in Air Traffic l Volume 7 71 Technical and Aircraft Equipment
41 (TD) AIRCRAFT DEFECTS. 42 (TM) SCHEDULED MAINTENANCE, late release. 43 (TN) NON-SCHEDULED MAINTENANCE, special checks and/or additional works beyond normal maintenance schedule. 44 (TS) SPARES AND MAINTENANCE EQUIPMENT, lack of or breakdown. 45 (TA) AOG SPARES, to be carried to another station. 46 (TC) AIRCRAFT CHANGE, for technical reasons. 47 (TL) STAND-BY AIRCRAFT, lack of planned stand-by aircraft for technical reasons. 48 (TV) SCHEDULED CABIN CONFIGURATION/VERSION ADJUSTMENTS.
Damage to Aircraft & EDP/Automated Equipment Failure
51 (DF) DAMAGE DURING FLIGHT OPERATIONS, bird or lightning strike, turbulence, heavy or overweight landing, collision during taxiing 52 (DG) DAMAGE DURING GROUND OPERATIONS, collisions (other than during taxiing), loading/off-loading damage, contamination, towing, extreme weather conditions 55 (ED) DEPARTURE CONTROL 56 (EC) CARGO PREPARATION/DOCUMENTATION 57 (EF) FLIGHT PLANS
Flight Operations and Crewing
61 (FP) FLIGHT PLAN, late completion or change of, flight documentation 62 (FF) OPERATIONAL REQUIREMENTS, fuel, load alteration 63 (FT) LATE CREW BOARDING OR DEPARTURE PROCEDURES, other than connection and standby (flight deck or entire crew) 64 (FS) FLIGHT DECK CREW SHORTAGE, sickness, awaiting standby, flight time limitations, crew meals, valid visa, health documents, etc. 65 (FR) FLIGHT DECK CREW SPECIAL REQUEST, not within operational requirements 66 (FL) LATE CABIN CREW BOARDING OR DEPARTURE PROCEDURES, other than connection and standby 67 (FC) CABIN CREW SHORTAGE, sickness, awaiting standby, flight time limitations, crew meals, valid visa, health documents, etc. 68 (FA) CABIN CREW ERROR OR SPECIAL REQUEST, not within operational requirements 69 (FB) CAPTAIN REQUEST FOR SECURITY CHECK, extraordinary
Weather
71 (WO) DEPARTURE STATION 72 (WT) DESTINATION STATION 73 (WR) EN ROUTE OR ALTERNATE 75 (WI) DE-ICING OF AIRCRAFT, removal of ice and/or snow, frost prevention excluding unserviceability of equip- ment 76 (WS) REMOVAL OF SNOW, ICE, WATER AND SAND FROM AIRPORT 77 (WG) GROUND HANDLING IMPAIRED BY ADVERSE WEATHER CONDITIONS
72 Planning for Delay: influence of flight scheduling on airline punctuality Trends in Air Traffic l Volume 7 Air Traffic Flow Management restrictions
81 (AT) ATFM due to ATC EN-ROUTE demand/capacity, standard demand/capacity problems 82 (AX) ATFM due to ATC STAFF/equipment EN-ROUTE, reduced capacity caused by industrial action or staff shor- tage, equipment failure, military exercise or extraordinary demand due to capacity reduction in neighbou- ring area 83 (AE) ATFM due to Restriction at Destination airport, airport and/or runway closed due to obstruction, industrial action, staff shortage, political unrest, noise abatement, night curfew, special flights 84 (AW) ATFM due to weather at Destination
Airport and Governmental Authorities
85 (AS) MANDATORY SECURITY 86 (AG) immigration, customs, health 87 (AF) airport facilities, parking stands, ramp congestion, lighting, buildings, gate limitations, etc. 88 (AD) Restrictions at airport of Destination, airport and/or runway closed due to obstruction, industrial action, staff shortage, political unrest, noise abatement, night curfew, special flights 89 (AM) Restrictions at airport of Departure with or without atfm restrictions, including Air Traffic Services, start-up and pushback, airport and/or runway closed due to obstruction or weather1, industrial action, staff shortage, political unrest, noise abatement, night curfew, special flights
Reactionary
91 (RL) LOAD CONNECTION, awaiting load from another flight 92 (RT) THROUGH CHECK-IN ERROR, passenger and baggage 93 (RA) AIRCRAFT ROTATION, late arrival of aircraft from another flight or previous sector 94 (RS) CABIN CREW ROTATION, awaiting cabin crew from another flight 95 (RC) CREW ROTATION, awaiting crew from another flight (flight deck or entire crew) 96 (RO) OPERATIONS CONTROL, re-routing, diversion, consolidation, aircraft change for reasons other than technical
Miscellaneous
97 (MI) INDUSTRIAL ACTION WITH OWN AIRLINE 98 (MO) INDUSTRIAL ACTION OUTSIDE OWN AIRLINE, excluding ATS 99 (MX) OTHER REASON, not matching any code above
1 Restriction due to weather in case of ATFM regulation only, else refer to code 71 (WO)
Planning for Delay: influence of flight scheduling on airline punctuality Trends in Air Traffic l Volume 7 73 74 Planning for Delay: influence of flight scheduling on airline punctuality Trends in Air Traffic l Volume 7 Planning for Delay: influence of flight scheduling on airline punctuality Trends in Air Traffic l Volume 7 75 D. CODA Delaygroups based on IATA Delay codes
CODA Primary / Delaygroup Reactionary Description IATA Code
Passengers + Baggage 11-19 Cargo + Mail 21-29 Aircraft + Ramp Handling 31-39 AIrline Primary Technical + Aircraft Equipment 41-49 Aircraft Damage and Ops Computer failure. 51-59 Flight Operations 61-69 Other airline-related causes Others
ATFM due to Restriction at Destination Airport 83 Immigration, Customs, Health 86 Airport Facilities 87 Airport Primary Restriction at Destination Airport 88 Restriction at Airport of Departure, with or without ATFM 89
ATFM due to ATC En-Rte Demand Capacity 81 En-Route Primary ATFM due to ATC Staff / Equipment En-Route 82
Misc Primary Miscellaneous 98-99
Security Primary Mandatory Security 85
Weather 71-79 Weather Primary ATFM due to Weather at Destination 84
Reactionary Reactionary Reactionary Delays (Pax, crew, aircraft, load) 91-96
76 Planning for Delay: influence of flight scheduling on airline punctuality Trends in Air Traffic l Volume 7 E. 2009 Analysis of Taxi-Out Times at Airport of Departure1
Mean TXO Standard ICAO IATA Airport Name 10th Pctl Median 90th Pctl in minutes Deviation
CYUL YUL Montreal/Dorval 20 8 13 18 27
CYVR YVR Vancouver Intl 20 6 15 19 25
CYYC YYC Calgary Intl 18 8 11 17 28
CYYZ YYZ Toronto Intl/L.B. PE 18 8 12 17 25
DAAG ALG Alger 10 3 7 10 15
DGAA ACC Accra 10 5 5 8 16
DNMM LOS Lagos 15 6 10 14 22
DTMB MIR Monastir/Habib Bourg 11 3 8 11 16
DTTA TUN Tunis/Carthage 13 4 9 12 18
DTTJ DJE Djerba/Zarzis 12 4 8 11 17
EBAW ANR Antwerpen Deurne 7 3 5 7 10
EBBR BRU Brussels 12 4 8 11 17
EBCI CRL Charleroi 11 4 7 10 16
EDDB SXF Schoenefeld-Berlin 12 6 8 10 17
EDDC DRS Dresden 8 3 5 8 11
EDDF FRA Frankfurt 13 5 7 13 19
EDDG FMO Muenster-Osnabrueck 6 4 4 5 9
EDDH HAM Hamburg 9 4 5 8 14
EDDK CGN Cologne/Bonn 11 4 6 10 16
EDDL DUS Dusseldorf 12 5 7 11 18
EDDM MUC Munich 13 5 8 12 19
EDDN NUE Nurenberg 8 3 5 8 12
EDDP LEJ Leipzig/Halle 12 7 6 11 20
EDDR SCN Saarbrucken/Ensheim 5 2 3 5 7
EDDS STR Stuttgart 11 5 6 10 17
EDDT TXL Berlin-Tegel 11 4 7 10 14
EDDV HAJ Hanover 10 5 6 9 14
EDDW BRE Bremen 9 3 6 9 12
EDFH HHN Hahn 12 4 8 11 17
EDHL LBC Lubeck-Blankensee 8 3 5 8 12
EDLP PAD Paderborn Lippstadt 6 2 4 6 9
1 > 1000 observations by airport.
Planning for Delay: influence of flight scheduling on airline punctuality Trends in Air Traffic l Volume 7 77 Mean TXO Standard ICAO IATA Airport Name 10th Pctl Median 90th Pctl in minutes Deviation
EDLV NRN Niederrhein/Weeze 10 3 7 9 13
EDLW DTM Dortmund-Wickede 9 4 6 9 13
EDNY FDH Friedrichshafen 7 3 4 7 10
EDSB FKB Karlsruhe/Baden-Baden 8 4 4 7 13
EETN TLL Tallinn/Ulemiste 7 3 4 7 11
EFHK HEL Helsinki-Vantaa 10 4 7 9 14
EFKU KUO Kuopio 4 2 2 3 6
EFOU OUL Oulu 4 2 3 4 6
EFRO RVN Rovaniemi 8 3 6 7 10
EFTP TMP Tampere/Pirkkala 7 3 4 7 10
EFTU TKU Turku 5 3 3 5 8
EGAA BFS Belfast/Aldergrove 9 3 7 9 12
EGAC BHD Belfast/City Airport 9 3 6 8 12
EGAE LDY Londonderry/Eglinton 8 3 5 7 12
EGBB BHX Birmingham 12 4 8 11 17
EGCC MAN Manchester 15 6 9 14 21
EGCN DSA Doncaster Sheffield 11 5 8 10 15
EGFF CWL Cardiff 9 3 6 9 13
EGGD BRS Bristol/Lulsgate 10 3 6 9 13
EGGP LPL Liverpool 10 4 7 10 14
EGGW LTN London/Luton 12 5 8 11 18
EGHH BOH Bournemouth/Hurn 11 3 8 10 15
EGHI SOU Southampton 10 3 7 10 15
EGJB GCI Guernsey 6 3 3 5 9
EGJJ JER Jersey 10 3 7 10 13
EGKK LGW London/Gatwick 16 6 10 15 23
EGLC LCY London/City 11 5 5 10 17
EGLL LHR London/Heathrow 21 7 13 20 29
EGNJ HUY Humberside 8 3 5 8 12
EGNM LBA Leeds And Bradford 11 3 7 10 15
EGNS IOM Isle Of Man/Ronaldsw 9 3 6 8 12
EGNT NCL Newcastle 11 3 8 10 14
EGNV MME Teesside 10 4 7 10 14
EGNX EMA East Midlands 11 4 8 10 15
EGPD ABZ Aberdeen 11 4 7 10 15
EGPE INV Inverness 8 4 5 8 13
EGPF GLA Glasgow 11 3 8 10 15
EGPH EDI Edinburgh 12 4 8 11 16
78 Planning for Delay: influence of flight scheduling on airline punctuality Trends in Air Traffic l Volume 7 Mean TXO Standard ICAO IATA Airport Name 10th Pctl Median 90th Pctl in minutes Deviation
EGPK PIK Prestwick 9 3 6 9 13
EGPN DND Dundee 7 3 4 6 10
EGSH NWI Norwich 10 5 7 10 14
EGSS STN London/Stansted 13 5 8 12 19
EGTE EXT Exeter 10 3 7 9 13
EHAM AMS Amsterdam 14 6 8 13 20
EHEH EIN Eindhoven 10 4 6 10 15
EHRD RTM Rotterdam 8 3 4 8 11
EICK ORK Cork 9 3 6 8 12
EICM GWY Galway Carnmore 5 2 3 5 8
EIDW DUB Dublin 14 6 8 14 22
EIKN NOC Connaught 10 4 6 9 14
EIKY KIR Kerry/Farranfore 8 3 5 7 11
EINN SNN Shannon 11 3 9 10 14
EIWF WAT Waterford 5 2 3 5 7
EKAH AAR Aarhus/Tirstrup 5 3 3 5 8
EKBI BLL Billund 10 5 5 9 14
EKCH CPH Copenhagen/Kastrup 12 5 8 11 16
EKYT AAL Aalborg 7 3 5 6 10
ELLX LUX Luxembourg 9 3 5 9 13
ENAL AES Alesund/Vigra 7 4 5 6 9
ENAN ANX Andenes 3 1 2 2 4
ENAT ALF Alta 4 3 2 3 7
ENBL FDE Forde/Bringeland 3 1 2 2 3
ENBN BNN Bronnoysund 3 2 2 3 5
ENBO BOO Bodo 5 4 2 4 9
ENBR BGO Bergen/Flesland 8 4 5 8 11
ENBS BJF Batsfjord 2 1 2 2 3
ENCN KRS Kristiansand/Kjevik 8 7 4 6 12
ENEV EVE Evenes 7 5 3 7 11
ENFL FRO Floro 6 3 3 5 9
ENGM OSL Oslo/Gardermoen 11 6 6 10 17
ENHD HAU Haugesund/Karmoy 7 3 4 6 9
ENHF HFT Hammerfest 3 1 2 2 4
ENKB KSU Kristiansund/Kv 5 2 3 5 7
ENKR KKN Kirkenes/Hoybuktmoen 4 3 2 4 6
ENLK LKN Leknes 2 1 2 2 3
ENMH MEH Mehamn 2 1 1 2 3
Planning for Delay: influence of flight scheduling on airline punctuality Trends in Air Traffic l Volume 7 79 Mean TXO Standard ICAO IATA Airport Name 10th Pctl Median 90th Pctl in minutes Deviation
ENML MOL Molde 6 4 4 6 9
ENMS MJF Mosjoen/Kjaerstad 2 1 2 2 3
ENNA LKL Banak 3 1 2 2 4
ENNK NVK Narvik/Framnes 3 1 2 3 4
ENNM OSY Namsos 2 2 2 2 3
ENOV HOV Orsta/Volda 3 2 1 2 4
ENRA MQN Mo I Rana/Rossvoll 2 1 2 2 3
ENRM RVK Rorvik/Ryum 2 1 2 2 3
ENRY RYG Rygge 10 6 7 9 15
ENSD SDN Sandane/Anda 3 1 2 2 3
ENSG SOG Sogndal/Haukasen 2 1 2 2 3
ENSH SVJ Svolvaer/Helle 2 1 2 2 3
ENSK SKN Stokmarknes/Skagen 2 1 1 2 3
ENSN SKE Skien/Geiteryggen 3 1 2 3 4
ENSS VAW Vardo/Svartnes 2 1 2 2 3
ENST SSJ Sandnessjoen/Stokka 2 1 1 2 3
ENTC TOS Tromso/Langnes 7 5 3 6 10
ENTO TRF Sandefjord/Torp 10 6 5 9 15
ENVA TRD Trondheim/Vaernes 7 4 4 7 10
ENVD VDS Vadso 3 1 2 3 4
ENZV SVG Stavanger/Sola 9 4 6 8 11
EPGD GDN Gdansk/Rebiechowo 9 4 5 9 13
EPKK KRK Krakow/Balice 9 3 5 8 13
EPKT KTW Katowice/Pyrzowice 12 5 7 10 17
EPPO POZ Poznan/Lawica 10 4 6 9 14
EPRZ RZE Rzeszow/Jasionka 7 3 5 7 11
EPSC SZZ Szczecin/Goleniow 8 2 5 7 11
EPWA WAW Warsaw/Okecie 12 5 7 11 17
EPWR WRO Wroclaw/Strachowice 9 4 5 8 13
ESGG GOT Gotenborg/Landvetter 9 3 6 8 12
ESGP GSE Goteborg-Save 7 3 4 6 10
ESKN NYO Stockholm/Skavsta 9 3 6 8 13
ESMS MMX Malmoe/Sturup 8 2 5 7 10
ESNN SDL Sundsvall/Harnosand 8 2 6 7 9
ESNU UME Umea 5 2 4 5 7
ESNZ OSD Ostersund Froesoe 5 1 4 5 6
ESPA LLA Lulea/Kallax 8 4 5 7 13
ESSA ARN Stockholm/Arlanda 10 4 7 9 14
80 Planning for Delay: influence of flight scheduling on airline punctuality Trends in Air Traffic l Volume 7 Mean TXO Standard ICAO IATA Airport Name 10th Pctl Median 90th Pctl in minutes Deviation
ESSB BMA Stockholm-Bromma 7 2 5 7 10
EVRA RIX Riga Intl 9 4 5 9 14
EYKA KUN Kaunas Intl 8 4 4 8 13
EYPA PLQ Palanga Intl 5 1 4 5 6
EYVI VNO Vilnius Intl 9 4 4 8 13
FACT CPT Cape Town 13 6 7 13 20
FAJS JNB Johannesburg/J.Smuts 16 5 11 16 23
GCFV FUE Fuerteventura 10 3 8 10 13
GCLP LPA Las Palmas 11 4 8 11 15
GCRR ACE Arrecife Lanzarote 10 3 7 9 13
GCTS TFS Tenerife Sur/Reina Sofia 10 3 7 10 14
GCXO TFN Tenerife Norte 10 3 7 10 13
GEML MLN Melilla 5 2 4 5 7
GMAD AGA Agadir/Al-Massira 8 3 5 8 11
GMFF FEZ Fes/Saiss 9 4 5 8 15
GMFO OUD Oujda/Angads 7 3 5 6 10
GMME RBA Rabat/Sale 8 3 5 7 12
GMMN CMN Casablanca/Mohammed V 13 4 10 12 18
GMMX RAK Marrakech 11 4 7 10 17
GMTT TNG Tanger/Boukhalf 9 10 6 8 12
GOOY DKR Dakar 15 4 10 14 20
HECA CAI Cairo 16 6 10 15 24
HEGN HRG Hurghada 14 4 10 13 19
HESH SSH Sharm El Sheikh 11 5 6 10 17
HKJK NBO Nairobi 14 4 10 13 18
HLLT TIP Tripoli 12 4 9 12 18
KATL ATL Atlanta Intl/Hartsfi 23 11 14 21 34
KBOS BOS Boston 18 6 12 17 25
KDFW DFW Dallas/Fort Worth 18 8 13 17 24
KEWR EWR Newark 29 14 15 25 46
KIAD IAD Washington 22 15 13 18 30
KIAH IAH Houston Intl/Texas 21 8 14 19 30
KJFK JFK New York 37 21 18 31 62
KLAX LAX Los Angeles 17 5 12 16 23
KMIA MIA Miami Intl/Florida 19 7 13 18 26
KORD ORD Chicago O Hare Intl 21 10 12 18 31
KPHL PHL Philadelphia 34 20 16 29 58
KSEA SEA Seattle/Tacoma Intl 17 7 12 16 21
Planning for Delay: influence of flight scheduling on airline punctuality Trends in Air Traffic l Volume 7 81 Mean TXO Standard ICAO IATA Airport Name 10th Pctl Median 90th Pctl in minutes Deviation
KSFO SFO San Francisco 22 5 17 22 29
LATI TIA Tirana 10 4 6 9 15
LBBG BOJ Burgas 8 3 5 8 11
LBSF SOF Sofia 12 5 8 11 17
LBWN VAR Varna 11 4 6 10 15
LCLK LCA Larnaca 10 4 5 10 15
LCPH PFO Paphos 9 3 5 8 13
LDDU DBV Dubrovnik 9 3 6 9 12
LDPL PUY Pula 9 3 5 9 12
LDSP SPU Split 8 3 6 8 11
LDZA ZAG Zagreb 8 3 5 8 13
LDZD ZAD Zadar 7 3 4 6 10
LEAL ALC Alicante 10 3 7 10 13
LEAM LEI Almeria 7 3 5 7 10
LEAS OVD Asturias 6 2 4 5 10
LEBB BIO Bilbao 8 3 5 8 11
LEBL BCN Barcelona 15 5 10 15 21
LEBZ BJZ Badajoz 7 2 5 7 10
LECO LCG La Coruna 8 3 5 8 11
LEGE GRO Gerona 10 2 8 10 13
LEGR GRX Granada 7 3 4 6 12
LEIB IBZ Ibiza 8 3 5 7 11
LEJR XRY Jerez De La Frontera 10 3 7 10 12
LELC MJV Murcia San Javier 8 3 5 7 11
LELN LEN Leon 7 2 5 7 9
LEMD MAD Madrid/Barajas 16 6 10 16 23
LEMG AGP Malaga 11 4 7 10 15
LEMH MAH Mahon 8 3 5 8 11
LEPA PMI Palma De Mallorca 11 4 6 10 16
LEPP PNA Noain Pamplona 6 2 4 5 8
LERS REU Reus 10 3 7 10 15
LESO EAS San Sebastian 6 2 4 5 9
LEST SCQ Santiago 8 3 5 8 12
LEVC VLC Valencia 9 3 5 9 13
LEVD VLL Valladolid 7 4 5 5 10
LEVX VGO Vigo 8 4 5 8 12
LEXJ SDR Santander 7 3 5 5 10
LEZG ZAZ Zaragoza 8 4 5 7 13
82 Planning for Delay: influence of flight scheduling on airline punctuality Trends in Air Traffic l Volume 7 Mean TXO Standard ICAO IATA Airport Name 10th Pctl Median 90th Pctl in minutes Deviation
LEZL SVQ Sevilla 8 3 5 8 12
LFBD BOD Bordeaux/Merignac 9 3 6 9 13
LFBE EGC Bergerac/Roumaniere 8 3 5 8 12
LFBL LIG Limoges Bellegarde 7 3 4 5 10
LFBO TLS Toulouse/Blagnac 10 3 7 10 12
LFBP PUF Pau Vzein 8 3 5 8 11
LFBT LDE Tarbes Ossun Lourdes 12 3 8 11 16
LFBZ BIQ Biarritz-Bayonne 9 3 6 8 12
LFCR RDZ Rodez Marcillac 7 2 4 6 10
LFJL ETZ Metz/Nancy 7 2 5 6 10
LFKB BIA Bastia 6 3 4 6 9
LFKJ AJA Ajaccio 7 3 5 7 11
LFLC CFE Clermont-Ferrand 6 2 4 5 8
LFLL LYS Lyon/Sartolas 11 4 7 10 16
LFLS GNB Grenoble 9 3 5 10 11
LFMK CCF Carcassonne Salvaza 10 4 6 10 15
LFML MRS Marseille/Provence 11 3 7 10 15
LFMN NCE Nice 11 3 7 10 15
LFMP PGF Perpignan Rivesaltes 7 3 4 6 10
LFMT MPL Montpellier 9 7 6 9 12
LFOB BVA Beauvais-Tille 10 3 7 10 14
LFPB LBG Paris/Le Bourget 9 4 6 9 13,5
LFPG CDG Paris/Charles-De-Gaulle 17 7 10 16 25
LFPO ORY Paris/Orly 12 5 8 11 18
LFQQ LIL Lille/Lesquin 9 3 5 8 12
LFRB BES Brest-Guipavas 10 3 7 9 13
LFRH LRT Lorient Lann Bihque 8 3 5 8 11
LFRN RNS Rennes Saint Jacques 6 3 4 5 10
LFRQ UIP Quimper Pluguffan 8 3 5 7 10
LFRS NTE Nantes 8 3 5 8 12
LFSB BSL Basle/Mulhouse 11 3 8 11 15
LFST SXB Strasbourg/Entzheim 7 3 4 7 10
LFTH TLN Hyeres La Palyvestre 10 3 8 10 13
LGAL AXD Dimokritos 9 4 5 9 15
LGAV ATH Athens 13 4 8 13 19
LGHI JKH Chios 7 3 5 6 11
LGIR HER Iraklion/Nikos/Kazantzakis 9 4 5 9 14
LGKF EFL Kefallinia 8 4 5 7 13
Planning for Delay: influence of flight scheduling on airline punctuality Trends in Air Traffic l Volume 7 83 Mean TXO Standard ICAO IATA Airport Name 10th Pctl Median 90th Pctl in minutes Deviation
LGKO KGS Kos 8 3 5 7 12
LGKP AOK Karpathos 6 2 5 5 8
LGKR CFU Ioannis/Kapodistrias 8 7 5 7 12
LGKV KVA Megas/Alexandros 7 3 5 7 10
LGLM LXS Limnos 7 3 5 5 10
LGMK JMK Mikonos 7 3 4 6 11
LGMT MJT Mitilini 7 4 5 7 10
LGPZ PVK Preveza/Levkas Aktio 6 4 3 5 10
LGRP RHO Diagoras 8 3 5 8 12
LGSA CHQ Khania/Souda 10 6 5 9 15
LGSM SMI Samos 7 3 4 6 11
LGSR JTR Santorini 7 3 4 6 12
LGTS SKG Makedonia 10 4 5 10 15
LGZA ZTH Zakinthos 8 5 4 6 15
LHBP BUD Budapest/Ferihegy 9 4 5 9 13
LIBD BRI Bari Palese 11 4 6 10 16
LIBP PSR Pescara 10 4 5 10 15
LIBR BDS Brindisi Casale 9 4 5 9 14
LICA SUF Lamezia Terme 9 4 5 8 14
LICC CTA Catania Fontanarossa 12 5 8 11 19
LICD LMP Lampedusa 7 3 4 6 10
LICG PNL Pantelleria 8 3 5 7 12
LICJ PMO Palermo Punta Raisi 11 3 8 10 15
LICR REG Reggio Calabria 8 4 4 7 12
LICT TPS Trapani Birgi 8 4 5 8 13
LIEA AHO Alghero 11 3 7 10 15
LIEE CAG Cagliari Elmas 12 4 8 11 17
LIEO OLB Olbia Costa Smeralda 11 4 7 10 17
LIMC MXP Milan/Malpensa 12 6 8 11 18
LIME BGY Bergamo/Orio Alserio 13 4 8 12 18
LIMF TRN Torino/Caselle 10 3 6 10 14
LIMJ GOA Genova Sestri 10 4 6 10 15
LIML LIN Milan/Linate 12 6 7 11 19
LIPE BLQ Bologna 11 3 7 10 15
LIPH TSF Treviso San Angelo 12 5 7 11 18
LIPO VBS Brescia/Montichiari 10 4 6 10 15
LIPQ TRS Ronchi Dei Legionari 9 4 5 9 15
LIPX VRN Verona Villafranca 11 5 5 10 17
84 Planning for Delay: influence of flight scheduling on airline punctuality Trends in Air Traffic l Volume 7 Mean TXO Standard ICAO IATA Airport Name 10th Pctl Median 90th Pctl in minutes Deviation
LIPY AOI Ancona Falconara 8 4 4 7 13
LIPZ VCE Venice/Tessera 10 4 7 10 15
LIRA CIA Rome/Ciampino 11 4 7 11 16
LIRF FCO Rome/Fiumicino 17 8 10 15 27
LIRN NAP Napoli Capodichino 11 4 6 10 15
LIRP PSA Pisa San Giusto 14 6 8 13 21
LIRQ FLR Firenze/Peretola 10 4 5 9 15
LJLJ LJU Ljubljana 9 4 5 8 13
LKMT OSR Ostrava 5 2 3 5 9
LKPR PRG Prague/Ruzyne 10 5 5 10 16
LKTB BRQ Brno Turany 6 3 3 5 10
LLBG TLV Tel Aviv/Ben Gurion 19 6 12 18 25
LMML MLA Malta/Luqa 8 4 5 7 12
LOWG GRZ Graz 7 3 4 6 10
LOWI INN Innsbruck 6 3 4 5 10
LOWK KLU Klagenfurt 5 2 3 4 8
LOWL LNZ Linz 6 2 4 5 8
LOWS SZG Salzburg 6 2 4 6 9
LOWW VIE Vienna 10 5 5 9 16
LPFR FAO Faro 10 3 8 10 14
LPHR HOR Horta Faial 5 2 2 4 8
LPLA TER Lajes Terceira 6 4 2 5 10
LPMA FNC Funchal Madeira 8 3 5 8 11
LPPD PDL Ponta Delgada 7 4 3 7 12
LPPR OPO Porto 11 4 7 10 16
LPPS PXO Porto Santo/Madeira 5 2 3 5 9
LPPT LIS Lisbon 12 5 8 11 18
LQSA SJJ Sarajevo 10 4 6 10 15
LRBS BBU Baneasa-Bucuresti 7 3 5 6 10
LRCL CLJ Cluj-Napoca/Someseni 9 4 5 9 13
LROP OTP Otopeni-Intl. 10 4 5 10 15
LRTR TSR Timisoara/Giarmata 9 5 5 7 15
LSGG GVA Geneva 11 4 7 10 16
LSZA LUG Lugano 7 2 5 7 9
LSZB BRN Bern 6 3 3 5 10
LSZH ZRH Zurich 11 5 6 10 17
LSZR ACH Altenrhein 6 2 4 5 9
LTAC ESB Ankara-Esenboga 13 4 9 12 17
Planning for Delay: influence of flight scheduling on airline punctuality Trends in Air Traffic l Volume 7 85 Mean TXO Standard ICAO IATA Airport Name 10th Pctl Median 90th Pctl in minutes Deviation
LTAF ADA Adana-Sakirpasa 11 3 8 10 15
LTAI AYT Antalya 16 7 10 15 22
LTAJ GZT Gaziantep 9 3 5 10 14
LTAN KYA Konya/Mil* 14 5 9 14 20
LTAT MLX Malatya-Erhac 11 4 7 10 15
LTAU ASR Kayser-Erkilet/Mil* 14 6 10 15 20
LTBA IST Istanbul/Ataturk 18 8 10 16 28
LTBJ ADB Izmir-Adnan-Menderes 12 3 9 11 16
LTBS DLM Mugla-Dalaman 11 4 8 10 15
LTCC DIY Diyar-Bakir 12 4 8 11 18
LTCE ERZ Erzurum 11 3 8 10 14
LTCG TZX Trabzon 10 3 7 10 13
LTCI VAN Van 11 2 9 10 13
LTFE BJV Milas/Bodrum 10 4 7 10 15
LTFH SZF Samsun-Carsamba 12 3 9 11 15
LTFJ SAW Istanbul Sabiha Gökçen 12 3 9 11 15
LUKK KIV Kishinev 10 4 6 9 15
LWSK SKP Skopje 9 4 5 8 12
LXGB GIB Gibraltar 12 4 8 12 16
LYBE BEG Surcin-Beograd 10 5 6 9 14
LZIB BTS Bratislava Ivanka 8 4 3 8 13
LZKZ KSC Kosice 5 3 2 5 8
MDPC PUJ Punta Cana 15 6 10 14 21
MMMX MEX Mexico City 21 7 15 19 29
MMUN CUN Cancun Intl 16 6 10 15 22
MUHA HAV Habana Intl/Jose Mar 16 6 12 15 21
OBBI BAH Bahrain-Intl 17 6 11 16 24
OEJN JED Jeddah 19 4 14 20 24
OEMA MED Madinah 13 5 10 10 18
OERK RUH Riyadh King Khalid 15 4 11 15 20
OIIE IKA Tehran 15 6 10 14 20
OJAI AMM Amman/Queen Alia 14 4 10 13 18
OKBK KWI Kuwait 18 8 12 16 26
OLBA BEY Beirut 12 4 9 11 16
OMAA AUH Abu Dhabi Intl 16 5 11 14 21
OMDB DXB Dubai 18 6 12 17 25
OSDI DAM Damascus 11 4 7 10 16
OTBD DOH Doha 17 6 11 15 25
86 Planning for Delay: influence of flight scheduling on airline punctuality Trends in Air Traffic l Volume 7 Mean TXO Standard ICAO IATA Airport Name 10th Pctl Median 90th Pctl in minutes Deviation
RJAA NRT New Tokyo 20 8 13 18 28
RJBB KIX Kansai Intl 15 4 11 14 19
RKSI ICN Seoul-Incheon International 18 6 13 17 23
SAEZ EZE Buenos Aires/Ezeiza 17 6 11 16 24
SBGL GIG Rio De Janeiro 19 9 12 17 28
SBGR GRU Sao Paulo 18 6 12 16 25
SVMI CCS Caracas Maiquetia 17 8 10 15 26
UAAA ALA Alma Ata 16 7 10 14 25
UBBB GYD Baku 12 4 7 11 15
UGTB TBS Tbilisi-Novo Alexeyevka 13 5 8 12 20
UKBB KBP Kiev - Borispol 13 6 7 12 20
UKLL LWO Lvov 9 3 5 9 13
UKOO ODS Odessa 11 5 5 10 20
ULLI LED Sankt-Peterburg 13 7 7 12 22
UMMS MSQ Minsk-2 12 6 7 11 20
UUDD DME Moskva/Domodedovo 17 8 11 15 26
UUEE SVO Moskva/Sheremetyevo 19 9 11 17 30
VABB BOM Bombay 18 6 12 16 25
VHHH HKG Hong Kong Intl 21 6 15 20 27
VIDP DEL Delhi 22 7 15 21 30
WSSS SIN Singapore/Changi 18 6 12 17 25
ZBAA PEK Beijing 23 10 14 21 32
ZSPD PVG Shanghai Pudong Intl 22 9 14 20 30
Planning for Delay: influence of flight scheduling on airline punctuality Trends in Air Traffic l Volume 7 87 F. 2009 Analysis of Taxi-In Times at Airport of Destination1
Mean TXI Standard ICAO IATA Airport Name 10th Pctl Median 90th Pctl in minutes Deviation
CYUL YUL Montreal/Dorval 8 5 4 6 12
CYVR YVR Vancouver Intl 7 2 5 6 9
CYYC YYC Calgary Intl 8 4 5 7 11
CYYZ YYZ Toronto Intl/L.B. PE 10 6 6 10 13
DAAG ALG Alger 6 2 4 5 8
DNMM LOS Lagos 10 3 7 10 13
DTMB MIR Monastir/Habib Bourg 4 2 3 3 7
DTTA TUN Tunis/Carthage 5 1 3 4 6
DTTJ DJE Djerba/Zarzis 5 2 3 4 7
EBAW ANR Antwerpen Deurne 5 3 2 5 7
EBBR BRU Brussels 5 2 3 5 7
EBCI CRL Charleroi 7 2 4 7 9
EDDB SXF Schoenefeld-Berlin 6 2 4 6 8
EDDC DRS Dresden 4 1 3 4 5
EDDF FRA Frankfurt 7 3 3 6 10
EDDG FMO Muenster-Osnabrueck 5 1 3 4 6
EDDH HAM Hamburg 4 2 3 4 6
EDDK CGN Cologne/Bonn 5 2 3 5 8
EDDL DUS Dusseldorf 5 2 3 4 7
EDDM MUC Munich 5 2 3 5 7
EDDN NUE Nurenberg 4 1 2 4 6
EDDP LEJ Leipzig/Halle 6 2 4 5 10
EDDR SCN Saarbrucken/Ensheim 5 1 3 4 6
EDDS STR Stuttgart 5 2 3 5 8
EDDT TXL Berlin-Tegel 4 2 3 4 6
EDDV HAJ Hanover 5 2 3 5 8
EDDW BRE Bremen 4 1 2 4 5
EDFH HHN Hahn 5 2 5 5 6
EDHL LBC Lubeck-Blankensee 4 2 3 4 6
EDLP PAD Paderborn Lippstadt 4 2 3 4 5
EDLV NRN Niederrhein/Weeze 5 2 5 5 5
1 > 1000 observations by airport.
88 Planning for Delay: influence of flight scheduling on airline punctuality Trends in Air Traffic l Volume 7 Mean TXI Standard ICAO IATA Airport Name 10th Pctl Median 90th Pctl in minutes Deviation
EDLW DTM Dortmund-Wickede 5 2 3 5 7
EDNY FDH Friedrichshafen 6 2 4 5 8
EDSB FKB Karlsruhe/Baden-Baden 5 2 3 5 7
EETN TLL Tallinn/Ulemiste 5 2 3 5 7
EFHK HEL Helsinki-Vantaa 4 2 2 4 7
EFKU KUO Kuopio 2 1 1 2 3
EFOU OUL Oulu 3 1 1 2 4
EFRO RVN Rovaniemi 3 1 2 3 5
EFTP TMP Tampere/Pirkkala 3 1 2 3 5
EFTU TKU Turku 4 2 2 4 5
EGAA BFS Belfast/Aldergrove 5 2 3 4 6
EGAC BHD Belfast/City Airport 4 2 2 4 6
EGAE LDY Londonderry/Eglinton 5 1 5 5 6
EGBB BHX Birmingham 7 3 4 6 10
EGCC MAN Manchester 7 4 4 7 11
EGCN DSA Doncaster Sheffield 5 3 3 5 7
EGFF CWL Cardiff 5 3 3 5 7
EGGD BRS Bristol/Lulsgate 4 2 2 4 6
EGGP LPL Liverpool 4 2 3 4 5
EGGW LTN London/Luton 5 3 3 5 7
EGHH BOH Bournemouth/Hurn 5 2 4 5 7
EGHI SOU Southampton 4 2 2 4 6
EGJB GCI Guernsey 5 3 3 5 7
EGJJ JER Jersey 5 2 3 5 7
EGKK LGW London/Gatwick 8 3 4 7 11
EGLC LCY London/City 4 2 2 3 5
EGLL LHR London/Heathrow 8 6 4 7 13
EGNJ HUY Humberside 4 1 3 4 5
EGNM LBA Leeds And Bradford 4 2 3 4 6
EGNS IOM Isle Of Man/Ronaldsw 4 2 2 4 6
EGNT NCL Newcastle 4 2 2 4 6
EGNV MME Teesside 4 1 3 5 5
EGNX EMA East Midlands 4 2 3 5 6
EGPD ABZ Aberdeen 5 2 3 4 7
EGPE INV Inverness 4 2 2 4 6
EGPF GLA Glasgow 5 2 3 4 7
EGPH EDI Edinburgh 5 3 3 5 8
EGPK PIK Prestwick 4 1 2 3 6
Planning for Delay: influence of flight scheduling on airline punctuality Trends in Air Traffic l Volume 7 89 Mean TXI Standard ICAO IATA Airport Name 10th Pctl Median 90th Pctl in minutes Deviation
EGPN DND Dundee 3 1 3 3 4
EGSH NWI Norwich 4 2 3 4 6
EGSS STN London/Stansted 8 3 4 8 10
EGTE EXT Exeter 4 3 2 4 6
EHAM AMS Amsterdam 8 4 3 7 14
EHEH EIN Eindhoven 6 2 3 6 9
EHRD RTM Rotterdam 5 3 3 5 7
EICK ORK Cork 5 2 4 5 6
EICM GWY Galway Carnmore 5 0 5 5 5
EIDW DUB Dublin 6 3 4 5 9
EIKN NOC Connaught 5 3 3 5 7
EIKY KIR Kerry/Farranfore 5 1 3 5 5
EINN SNN Shannon 5 2 4 5 7
EIWF WAT Waterford 5 0 5 5 5
EKAH AAR Aarhus/Tirstrup 4 1 3 4 5
EKBI BLL Billund 4 1 3 4 6
EKCH CPH Copenhagen/Kastrup 6 2 4 6 8
EKYT AAL Aalborg 5 1 3 5 6
ELLX LUX Luxembourg 4 2 3 4 6
ENAL AES Alesund/Vigra 3 1 1 3 4
ENAN ANX Andenes 2 1 2 2 3
ENAT ALF Alta 3 1 2 3 4
ENBL FDE Forde/Bringeland 2 0 2 2 2
ENBN BNN Bronnoysund 2 0 2 2 3
ENBO BOO Bodo 3 1 2 2 5
ENBR BGO Bergen/Flesland 4 2 2 3 5
ENBS BJF Batsfjord 2 0 2 2 2
ENCN KRS Kristiansand/Kjevik 3 1 2 3 4
ENEV EVE Evenes 3 1 2 3 4
ENFL FRO Floro 4 3 1 5 8
ENGM OSL Oslo/Gardermoen 4 2 2 4 6
ENHD HAU Haugesund/Karmoy 3 1 2 3 5
ENHF HFT Hammerfest 2 0 2 2 3
ENKB KSU Kristiansund/Kv 2 1 2 2 3
ENKR KKN Kirkenes/Hoybuktmoen 2 1 2 2 4
ENLK LKN Leknes 2 0 2 2 2
ENML MOL Molde 3 2 1 2 4
ENMS MJF Mosjoen/Kjaerstad 2 0 2 2 2
90 Planning for Delay: influence of flight scheduling on airline punctuality Trends in Air Traffic l Volume 7 Mean TXI Standard ICAO IATA Airport Name 10th Pctl Median 90th Pctl in minutes Deviation
ENNA LKL Banak 2 0 2 2 2
ENNK NVK Narvik/Framnes 2 0 2 2 2
ENNM OSY Namsos 2 0 2 2 2
ENOV HOV Orsta/Volda 1 0 1 1 2
ENRA MQN Mo I Rana/Rossvoll 2 0 2 2 2
ENRM RVK Rorvik/Ryum 2 0 2 2 2
ENRY RYG Rygge 4 2 3 4 5
ENSD SDN Sandane/Anda 2 1 1 2 2
ENSG SOG Sogndal/Haukasen 2 0 2 2 2
ENSH SVJ Svolvaer/Helle 2 0 1 2 2
ENSK SKN Stokmarknes/Skagen 2 1 1 2 2
ENSN SKE Skien/Geiteryggen 2 1 1 2 2
ENSS VAW Vardo/Svartnes 2 0 2 2 2
ENST SSJ Sandnessjoen/Stokka 2 0 1 2 2
ENTC TOS Tromso/Langnes 3 1 2 2 5
ENTO TRF Sandefjord/Torp 4 2 2 4 7
ENVA TRD Trondheim/Vaernes 3 2 2 3 4
ENVD VDS Vadso 2 0 2 2 2
ENZV SVG Stavanger/Sola 4 2 3 4 5
EPGD GDN Gdansk/Rebiechowo 3 1 2 3 4
EPKK KRK Krakow/Balice 7 2 5 7 10
EPKT KTW Katowice/Pyrzowice 4 2 2 4 6
EPPO POZ Poznan/Lawica 7 2 5 7 10
EPRZ RZE Rzeszow/Jasionka 7 2 5 6 10
EPSC SZZ Szczecin/Goleniow 7 1 6 7 8
EPWA WAW Warsaw/Okecie 5 2 3 4 7
EPWR WRO Wroclaw/Strachowice 7 2 6 7 9
ESGG GOT Gotenborg/Landvetter 4 1 3 4 5
ESGP GSE Goteborg-Save 4 1 3 4 5
ESKN NYO Stockholm/Skavsta 5 2 4 5 6
ESMS MMX Malmoe/Sturup 4 1 3 4 6
ESNN SDL Sundsvall/Harnosand 4 1 3 4 4
ESNU UME Umea 3 1 2 3 4
ESNZ OSD Ostersund Froesoe 4 1 2 4 5
ESPA LLA Lulea/Kallax 4 2 3 4 5
ESSA ARN Stockholm/Arlanda 5 2 3 5 8
ESSB BMA Stockholm-Bromma 4 1 4 4 6
EVRA RIX Riga Intl 5 2 3 5 6
Planning for Delay: influence of flight scheduling on airline punctuality Trends in Air Traffic l Volume 7 91 Mean TXI Standard ICAO IATA Airport Name 10th Pctl Median 90th Pctl in minutes Deviation
EYKA KUN Kaunas Intl 5 3 3 5 6
EYPA PLQ Palanga Intl 4 1 3 4 5
EYVI VNO Vilnius Intl 5 2 3 5 7
FACT CPT Cape Town 6 2 4 6 9
FAJS JNB Johannesburg/J.Smuts 10 3 6 10 13
GCFV FUE Fuerteventura 5 2 3 5 7
GCLP LPA Las Palmas 5 2 3 4 6
GCRR ACE Arrecife Lanzarote 4 2 3 4 6
GCTS TFS Tenerife Sur/Reina Sofia 5 2 3 5 7
GCXO TFN Tenerife Norte 4 3 2 4 5
GEML MLN Melilla 3 1 3 3 4
GMAD AGA Agadir/Al-Massira 6 2 4 5 7
GMFF FEZ Fes/Saiss 5 1 4 5 6
GMFO OUD Oujda/Angads 6 2 5 5 9
GMME RBA Rabat/Sale 5 4 4 5 7
GMMN CMN Casablanca/Mohammed V 6 3 4 5 8
GMMX RAK Marrakech 4 2 2 4 5
GMTT TNG Tanger/Boukhalf 6 2 4 5 9
GOOY DKR Dakar 7 5 5 7 10
HECA CAI Cairo 10 4 5 9 15
HEGN HRG Hurghada 5 2 3 5 7
HELX LXR Luxor 5 2 3 5 7
HESH SSH Sharm El Sheikh 5 3 3 5 8
HKJK NBO Nairobi 8 3 6 8 11
HLLT TIP Tripoli 5 2 3 5 8
KATL ATL Atlanta Intl/Hartsfi 9 5 6 8 14
KBOS BOS Boston 9 3 5 8 12
KDFW DFW Dallas/Fort Worth 9 5 4 9 15
KEWR EWR Newark 10 5 6 8 14
KIAD IAD Washington 8 3 5 7 11
KIAH IAH Houston Intl/Texas 7 3 5 7 11
KJFK JFK New York 12 7 5 11 20
KLAX LAX Los Angeles 13 6 8 12 20
KMIA MIA Miami Intl/Florida 8 5 4 6 12
KORD ORD Chicago O Hare Intl 9 5 5 8 14
KPHL PHL Philadelphia 5 4 3 4 10
KSEA SEA Seattle/Tacoma Intl 6 3 4 6 10
KSFO SFO San Francisco 9 4 6 8 13
92 Planning for Delay: influence of flight scheduling on airline punctuality Trends in Air Traffic l Volume 7 Mean TXI Standard ICAO IATA Airport Name 10th Pctl Median 90th Pctl in minutes Deviation
LATI TIA Tirana 5 1 4 5 7
LBBG BOJ Burgas 6 5 3 5 10
LBSF SOF Sofia 5 2 3 5 7
LBWN VAR Varna 6 2 4 5 10
LCLK LCA Larnaca 8 3 5 7 11
LCPH PFO Paphos 6 2 3 5 9
LDDU DBV Dubrovnik 4 1 2 4 5
LDPL PUY Pula 6 4 4 5 7
LDSP SPU Split 4 1 2 4 5
LDZA ZAG Zagreb 5 2 3 5 6
LDZD ZAD Zadar 5 1 4 5 6
LEAL ALC Alicante 5 1 3 5 6
LEAM LEI Almeria 5 1 4 5 6
LEAS OVD Asturias 5 1 4 5 7
LEBB BIO Bilbao 5 1 3 4 6
LEBL BCN Barcelona 5 3 3 5 9
LEBZ BJZ Badajoz 3 1 2 3 5
LECO LCG La Coruna 4 1 2 4 5
LEGE GRO Gerona 3 1 2 3 4
LEGR GRX Granada 4 1 3 4 6
LEIB IBZ Ibiza 4 2 3 4 6
LEJR XRY Jerez De La Frontera 5 1 4 5 6
LELC MJV Murcia San Javier 4 2 3 5 5
LELN LEN Leon 4 0 4 4 4
LEMD MAD Madrid/Barajas 9 4 5 9 13
LEMG AGP Malaga 4 2 3 4 6
LEMH MAH Mahon 4 2 2 4 5
LEPA PMI Palma De Mallorca 5 2 2 4 8
LEPP PNA Noain Pamplona 5 0 5 5 5
LERS REU Reus 4 2 2 4 6
LESO EAS San Sebastian 3 2 2 3 4
LEST SCQ Santiago 4 2 2 4 6
LEVC VLC Valencia 4 2 2 4 6
LEVD VLL Valladolid 5 2 4 5 6
LEVX VGO Vigo 3 1 2 3 5
LEXJ SDR Santander 5 1 3 5 5
LEZG ZAZ Zaragoza 6 2 4 5 7
LEZL SVQ Sevilla 4 2 3 5 5
Planning for Delay: influence of flight scheduling on airline punctuality Trends in Air Traffic l Volume 7 93 Mean TXI Standard ICAO IATA Airport Name 10th Pctl Median 90th Pctl in minutes Deviation
LFBD BOD Bordeaux/Merignac 5 1 3 5 7
LFBE EGC Bergerac/Roumaniere 5 2 3 4 6
LFBL LIG Limoges Bellegarde 6 2 3 5 10
LFBO TLS Toulouse/Blagnac 5 2 3 5 7
LFBP PUF Pau Vzein 4 1 3 4 5
LFBT LDE Tarbes Ossun Lourdes 5 2 4 5 7
LFBZ BIQ Biarritz-Bayonne 3 2 2 2 5
LFCR RDZ Rodez Marcillac 4 1 3 4 6
LFJL ETZ Metz/Nancy 3 2 2 2 5
LFKB BIA Bastia 4 1 3 4 5
LFKJ AJA Ajaccio 4 2 3 3 5
LFLC CFE Clermont-Ferrand 3 1 3 3 4
LFLL LYS Lyon/Sartolas 5 2 3 5 7
LFLS GNB Grenoble 5 4 2 5 6
LFMK CCF Carcassonne Salvaza 4 1 3 4 5
LFML MRS Marseille/Provence 5 2 3 5 7
LFMN NCE Nice 4 2 3 4 6
LFMP PGF Perpignan Rivesaltes 5 1 3 5 6
LFMT MPL Montpellier 4 1 3 3 5
LFOB BVA Beauvais-Tille 5 2 3 4 7
LFPB LBG Paris/Le Bourget 6 2 3 6 9
LFPG CDG Paris/Charles-De-Gaulle 10 4 6 9 14
LFPO ORY Paris/Orly 6 3 3 5 9
LFQQ LIL Lille/Lesquin 5 1 4 5 5
LFRB BES Brest-Guipavas 3 1 2 3 5
LFRH LRT Lorient Lann Bihque 5 1 4 5 7
LFRN RNS Rennes Saint Jacques 5 2 3 5 6
LFRQ UIP Quimper Pluguffan 4 1 3 3 5
LFRS NTE Nantes 4 2 2 4 5
LFSB BSL Basle/Mulhouse 4 1 3 5 5
LFST SXB Strasbourg/Entzheim 4 1 2 4 5
LFTH TLN Hyeres La Palyvestre 5 2 3 5 7
LGAL AXD Dimokritos 5 1 4 5 7
LGAV ATH Athens 6 3 3 5 10
LGHI JKH Chios 5 2 4 5 7
LGIR HER Iraklion/Nikos/Kazantzakis 5 2 3 5 7
LGKF EFL Kefallinia 5 2 3 5 6
LGKO KGS Kos 4 2 2 4 6
94 Planning for Delay: influence of flight scheduling on airline punctuality Trends in Air Traffic l Volume 7 Mean TXI Standard ICAO IATA Airport Name 10th Pctl Median 90th Pctl in minutes Deviation
LGKP AOK Karpathos 5 5 3 5 5
LGKR CFU Ioannis/Kapodistrias 4 3 3 4 6
LGKV KVA Megas/Alexandros 5 2 3 5 7
LGLM LXS Limnos 5 4 4 5 6
LGMK JMK Mikonos 5 2 3 5 7
LGMT MJT Mitilini 5 2 3 5 7
LGPZ PVK Preveza/Levkas Aktio 5 4 3 5 8
LGRP RHO Diagoras 5 2 3 5 7
LGSA CHQ Khania/Souda 5 3 3 5 7
LGSM SMI Samos 4 2 2 4 6
LGSR JTR Santorini 5 2 3 5 6
LGTS SKG Makedonia 6 2 4 5 8
LGZA ZTH Zakinthos 5 2 3 5 5
LHBP BUD Budapest/Ferihegy 4 2 2 4 6
LIBD BRI Bari Palese 5 2 3 5 7
LIBP PSR Pescara 6 2 4 6 7
LIBR BDS Brindisi Casale 7 2 4 7 9
LICA SUF Lamezia Terme 5 2 3 5 6
LICC CTA Catania Fontanarossa 5 2 3 5 7
LICD LMP Lampedusa 5 1 3 5 5
LICG PNL Pantelleria 6 2 5 6 8
LICJ PMO Palermo Punta Raisi 5 2 4 5 7
LICR REG Reggio Calabria 5 1 3 5 7
LICT TPS Trapani Birgi 6 2 4 5 8
LIEA AHO Alghero 5 1 3 5 6
LIEE CAG Cagliari Elmas 5 1 5 5 7
LIEO OLB Olbia Costa Smeralda 5 1 4 5 6
LIMC MXP Milan/Malpensa 6 3 3 5 10
LIME BGY Bergamo/Orio Alserio 4 1 3 5 5
LIMF TRN Torino/Caselle 7 3 4 7 11
LIMJ GOA Genova Sestri 6 2 5 6 8
LIML LIN Milan/Linate 5 1 3 5 5
LIPE BLQ Bologna 4 1 3 5 5
LIPH TSF Treviso San Angelo 5 1 5 5 5
LIPO VBS Brescia/Montichiari 6 2 4 5 8
LIPQ TRS Ronchi Dei Legionari 5 1 4 5 5
LIPX VRN Verona Villafranca 4 1 3 5 5
LIPY AOI Ancona Falconara 5 1 3 5 5
Planning for Delay: influence of flight scheduling on airline punctuality Trends in Air Traffic l Volume 7 95 Mean TXI Standard ICAO IATA Airport Name 10th Pctl Median 90th Pctl in minutes Deviation
LIPZ VCE Venice/Tessera 5 2 3 5 6
LIRA CIA Rome/Ciampino 5 1 3 5 5
LIRF FCO Rome/Fiumicino 8 3 5 8 12
LIRN NAP Napoli Capodichino 5 2 3 5 6
LIRP PSA Pisa San Giusto 5 2 3 5 7
LIRQ FLR Firenze/Peretola 5 1 3 5 6
LJLJ LJU Ljubljana 4 2 2 3 5
LKMT OSR Ostrava 5 2 3 5 6
LKPR PRG Prague/Ruzyne 5 2 3 5 8
LKTB BRQ Brno Turany 5 1 3 5 6
LLBG TLV Tel Aviv/Ben Gurion 6 3 4 6 9
LMML MLA Malta/Luqa 4 2 2 4 6
LOWG GRZ Graz 4 1 3 4 5
LOWI INN Innsbruck 3 1 3 3 4
LOWK KLU Klagenfurt 4 1 3 4 4
LOWL LNZ Linz 4 1 4 4 5
LOWS SZG Salzburg 5 1 3 4 5
LOWW VIE Vienna 5 2 3 5 8
LPFR FAO Faro 4 2 3 4 6
LPHR HOR Horta Faial 3 1 2 3 5
LPLA TER Lajes Terceira 4 2 2 3 6
LPMA FNC Funchal Madeira 4 2 2 3 5
LPPD PDL Ponta Delgada 3 1 2 3 5
LPPR OPO Porto 5 2 3 5 7
LPPS PXO Porto Santo/Madeira 3 1 2 3 5
LPPT LIS Lisbon 5 2 3 5 7
LQSA SJJ Sarajevo 4 2 3 4 5
LRBS BBU Baneasa-Bucuresti 6 3 4 5 8
LRCL CLJ Cluj-Napoca/Someseni 5 2 4 5 7
LROP OTP Otopeni-Intl. 7 2 5 7 9
LRTR TSR Timisoara/Giarmata 5 2 3 5 7
LSGG GVA Geneva 4 1 3 4 5
LSZA LUG Lugano 3 0 3 3 3
LSZB BRN Bern 3 1 3 3 3
LSZH ZRH Zurich 5 2 3 5 7
LSZR ACH Altenrhein 4 1 2 4 5
LTAC ESB Ankara-Esenboga 8 2 6 8 10
LTAF ADA Adana-Sakirpasa 6 2 5 5 8
96 Planning for Delay: influence of flight scheduling on airline punctuality Trends in Air Traffic l Volume 7 Mean TXI Standard ICAO IATA Airport Name 10th Pctl Median 90th Pctl in minutes Deviation
LTAI AYT Antalya 7 3 4 7 10
LTAJ GZT Gaziantep 5 1 5 5 5
LTAN KYA Konya/Mil* 10 1 10 10 10
LTAT MLX Malatya-Erhac 7 2 5 7 10
LTAU ASR Kayser-Erkilet/Mil* 5 1 5 5 5
LTBA IST Istanbul/Ataturk 7 3 4 7 11
LTBJ ADB Izmir-Adnan-Menderes 5 1 4 5 6
LTBS DLM Mugla-Dalaman 5 2 4 5 7
LTCC DIY Diyar-Bakir 6 2 4 5 9
LTCE ERZ Erzurum 5 2 4 5 7
LTCG TZX Trabzon 6 2 5 6 8
LTCI VAN Van 5 0 5 5 5
LTFE BJV Milas/Bodrum 6 2 4 5 8
LTFH SZF Samsun-Carsamba 6 2 5 5 8
LTFJ SAW Istanbul Sabiha Gökçen 6 2 4 5 8
LUKK KIV Kishinev 4 1 3 4 6
LWSK SKP Skopje 5 1 4 5 5
LXGB GIB Gibraltar 5 2 3 5 8
LYBE BEG Surcin-Beograd 5 2 3 5 7
LZIB BTS Bratislava Ivanka 4 3 3 4 6
LZKZ KSC Kosice 4 2 3 4 5
MDPC PUJ Punta Cana 6 6 3 5 9
MMMX MEX Mexico City 9 3 6 9 13
MMUN CUN Cancun Intl 8 8 3 5 12
MUHA HAV Habana Intl/Jose Mar 6 4 4 5 10
OBBI BAH Bahrain-Intl 6 4 3 5 8
OEJN JED Jeddah 12 5 8 10 16
OEMA MED Madinah 9 4 5 10 10
OERK RUH Riyadh King Khalid 7 4 4 6 10
OIIE IKA Tehran 8 3 5 8 10
OJAI AMM Amman/Queen Alia 7 3 5 7 10
OKBK KWI Kuwait 9 8 5 7 17
OLBA BEY Beirut 5 2 4 5 7
OMAA AUH Abu Dhabi Intl 6 4 4 5 11
OMDB DXB Dubai 9 3 5 8 12
OSDI DAM Damascus 6 2 4 5 9
OTBD DOH Doha 5 2 4 5 7
RJAA NRT New Tokyo 11 6 5 10 20
Planning for Delay: influence of flight scheduling on airline punctuality Trends in Air Traffic l Volume 7 97 Mean TXI Standard ICAO IATA Airport Name 10th Pctl Median 90th Pctl in minutes Deviation
RJBB KIX Kansai Intl 6 2 3 6 9
RKSI ICN Seoul-Incheon International Airport 8 2 5 8 10
SAEZ EZE Buenos Aires/Ezeiza 8 3 5 7 11
SBGL GIG Rio De Janeiro 10 3 7 9 13
SBGR GRU Sao Paulo 10 5 6 9 14
SVMI CCS Caracas Maiquetia 8 4 5 7 11
UAAA ALA Alma Ata 9 4 5 9 12
UBBB GYD Baku 6 2 4 5 8
UGTB TBS Tbilisi-Novo Alexeyevka 7 2 4 6 9
UKBB KBP Kiev - Borispol 7 3 4 6 10
UKLL LWO Lvov 5 2 3 5 8
UKOO ODS Odessa 7 3 4 6 10
ULLI LED Sankt-Peterburg 7 4 3 6 12
UMMS MSQ Minsk-2 5 2 3 5 7
UUDD DME Moskva/Domodedovo 8 3 5 7 10
UUEE SVO Moskva/Sheremetyev 7 4 4 7 11
VABB BOM Bombay 11 6 7 10 17
VHHH HKG Hong Kong Intl 7 2 4 7 10
VIDP DEL Delhi 12 8 5 10 21
WSSS SIN Singapore/Changi 7 2 4 6 10
ZBAA PEK Beijing 8 4 4 7 13
ZSPD PVG Shanghai Pudong Intl 8 4 5 8 12
98 Planning for Delay: influence of flight scheduling on airline punctuality Trends in Air Traffic l Volume 7 G. 2009 Taxi-Out Times by Wake Turbulence Category
Wake Mean TXO Standard ICAO IATA Airport Name Turbulence 10th Pctl Median 90th Pctl Category in minutes Deviation
H 16 7 11 15 23 EBBR BRU Brussels M 12 4 8 11 16
H 16 6 11 15 22 EDDF FRA Frankfurt M 13 5 7 12 19
H 11 4 7 10 15 EDDH HAM Hamburg M 9 4 5 8 14
EDDK CGN Cologne/Bonn M 11 4 6 10 16
H 15 6 10 14 21 EDDL DUS Dusseldorf M 12 5 7 11 18
H 18 7 12 16 25 EDDM MUC Munich M 13 5 8 12 19
EDDS STR Stuttgart M 11 5 6 10 17
H 12 5 8 11 16 EDDT TXL Berlin-Tegel M 11 4 7 10 14
H 12 3 9 11 16 EFHK HEL Helsinki-Vantaa M 10 4 7 9 14
H 14 4 10 14 18 EGBB BHX Birmingham M 12 4 8 11 17
H 18 6 13 17 24 EGCC MAN Manchester M 14 6 9 13 20
EGGW LTN London/Luton M 12 5 8 11 18
H 19 6 13 18 25 EGKK LGW London/Gatwick M 16 6 10 15 23
H 24 7 17 23 32 EGLL LHR London/Heathrow M 20 6 13 19 27
H 13 5 9 12 18 EGPF GLA Glasgow M 11 3 8 10 15
EGPH EDI Edinburgh M 12 4 8 11 16
H 14 4 10 13 20 EGSS STN London/Stansted M 13 5 8 12 19
H 18 7 12 16 24 EHAM AMS Amsterdam M 13 5 8 12 19
Planning for Delay: influence of flight scheduling on airline punctuality Trends in Air Traffic l Volume 7 99 Wake Mean TXO Standard ICAO IATA Airport Name Turbulence 10th Pctl Median 90th Pctl Category in minutes Deviation
H 18 7 11 16 24 EIDW DUB Dublin M 14 6 8 13 21
H 14 6 10 13 18 EKCH CPH Copenhagen/Kastrup M 12 5 7 11 16
ENBR BGO Bergen/Flesland M 8 4 5 8 11
H 15 8 9 13 26 ENGM OSL Oslo/Gardermoen M 11 6 6 10 17
H 17 6 12 16 22 EPWA WAW Warsaw/Okecie M 12 5 7 11 17
H 14 5 10 13 19 ESSA ARN Stockholm/Arlanda M 10 4 7 9 14
H 13 3 9 12 17 GCLP LPA Las Palmas M 11 4 7 11 15
H 22 9 14 21 32 LEBL BCN Barcelona M 15 5 10 15 21
H 17 7 11 16 25 LEMD MAD Madrid/Barajas M 16 6 10 16 23
H 14 5 9 13 19 LEMG AGP Malaga M 11 4 7 10 15
H 13 4 9 13 18 LEPA PMI Palma De Mallorca M 11 4 6 10 16
H 17 8 11 16 24 LFBO TLS Toulouse/Blagnac M 10 3 7 10 12
H 17 8 11 16 23 LFLL LYS Lyon/Sartolas M 11 4 7 10 16
H 15 4 11 15 20 LFML MRS Marseille/Provence M 11 3 7 10 15
H 15 4 12 15 20 LFMN NCE Nice M 11 3 7 10 15
H 22 9 14 20 30 LFPG CDG Paris/Charles-De-Gaulle M 16 7 10 15 23
H 19 8 13 18 27 LFPO ORY Paris/Orly M 12 4 8 10 17
H 15 5 10 14 20 LGAV ATH Athens M 13 4 8 13 19
H 17 9 9 13 31 LHBP BUD Budapest/Ferihegy M 9 4 5 9 13
H 19 8 12 17 28 LIMC MXP Milan/Malpensa M 12 6 7 11 17
100 Planning for Delay: influence of flight scheduling on airline punctuality Trends in Air Traffic l Volume 7 Wake Mean TXO Standard ICAO IATA Airport Name Turbulence 10th Pctl Median 90th Pctl Category in minutes Deviation
LIML LIN Milan/Linate M 12 6 7 11 19
H 24 10 13 22 36 LIRF FCO Rome/Fiumicino M 17 7 9 15 26
H 13 6 8 12 19 LKPR PRG Prague/Ruzyne M 10 5 5 10 16
H 19 5 13 19 25 LLBG TLV Tel Aviv/Ben Gurion M 18 6 12 18 25
H 15 7 10 13 21 LOWW VIE Vienna M 10 5 5 9 16
H 13 6 7 12 20 LPPT LIS Lisbon M 12 5 8 11 18
H 15 5 10 14 20 LSGG GVA Geneva M 11 4 7 10 16
H 17 7 11 15 24 LSZH ZRH Zurich M 11 5 6 10 16
H 18 5 11 17 25 LTAI AYT Antalya M 16 7 10 15 22
H 19 8 11 18 30 LTBA IST Istanbul/Ataturk M 17 8 10 15 28
UKBB KBP Kiev - Borispol M 13 6 7 12 20
UUEE SVO Moskva/Sheremetyev M 19 9 11 17 30
Planning for Delay: influence of flight scheduling on airline punctuality Trends in Air Traffic l Volume 7 101 Glossary
ACARS Aircraft Communications Addressing and Reporting System. This was developed to reduce the flight crew’s workload by using modern computer technology to exchange many routine reports and message and thus improve safety and efficiency of modern air travel.
ACARS is used for automated reporting of OOOI times (OUT-OFF-ON-IN; see glossary terms immediately below) bringing higher accuracy to delay reporting. There are still no defined standards used to define pre-set reference points for measuring OOOI times, but each airline policy selects and defines it. ACARS provides communication between Airline Operations and the flight crew in an aircraft.
IN Actual In (on block) Time in UTC (Coordinated Universal Time). This time can be recorded by ACARS, manually or via A-VDGS. If it is automatically recorded by ACARS that is the moment when an aircraft arrived at a stand and when its ground speed is equal to zero.
OFF Actual Take Off Time in UTC (Coordinated Universal Time). This time can be recorded by ACARS or manually. If it is auto- matically recorded by ACARS, that is the moment when an aircraft took off from the ground and if it is recorded manually, it could also be the moment when aircraft reached a certain height (e.g. 15m) or when it lined up for take-off.
ON Actual On Ground (landing) Time in UTC (Coordinated Universal Time). This time can be recorded by ACARS or manually. If it is automatically recorded by ACARS, that is the moment when an aircraft touched the ground for the first time and if it is recorded manually, it could also be the moment when the aircraft finished its landing on the runway, before leaving it.
OUT Actual Out (off block) Time in UTC (Coordinated Universal Time).This time can be recorded by ACARS, manually or via A-VDGS. If it is automatically recorded by ACARS that is the moment when a pilot released the brakes on the aircraft.
Since pilots used to release breaks early to prevent delays from being recorded a new generation of ACARS has sensors which are able to recognise ground speed of more than three knots indicating aircraft movement. If the time is recorded manually, it could also be the moment when the aircraft left the gate.
ADD Average Delay per Delayed Flight is the sum of all delay minutes (for all causes) in departure divided by the number of delayed flights.
ADEP Airport of Departure, the ICAO airport code or location indicator is a four-letter alphanumeric code designating each airport around the world. These codes are defined by the International Civil Aviation Organisation (ICAO), and published in ICAO Docu- ment 7910: Location Indicators. It is important to note that the same airport can have a different ICAO designator depending on the terminal. This is the case with large airports i.e. Brussels airport has two ICAO designators depending on the terminal. For military terminals the ICAO designator is EBMB and for civil terminals the ICAO designator EBBR is used.
ADES Airport of Destination, the ICAO airport code or location indicator is a four-letter alphanumeric code designating each airport around the world. These codes are defined by the International Civil Aviation Organisation, and published in ICAO Document 7910: Location Indicators. It is important to note that the same airport can have a different ICAO designator depending on the terminal. This is the case with large airports i.e. Brussels airport has two ICAO designators depending on the terminal. For military terminals the ICAO designator is EBMB and for civil terminals the ICAO designator EBBR is used.
102 Planning for Delay: influence of flight scheduling on airline punctuality Trends in Air Traffic l Volume 7 ADM Average Delay Per Movement is equal to the sum of all delay minutes in departure (TDMD) divided by the TTF (Total Operated Flights). Flights leaving ahead of schedule are delay neutral.
ADM (ATFM) Average AFTM Delay Minutes is equal to TDM (Total ATFM Delay Minutes) divided by the TTF (Total Operated Flights). Flights leaving ahead of schedule are delay neutral.
AHM The IATA Airport Handling Manual has been developed to assist the industry in the provision of safe, effective and quality services at lower costs. It covers: airside safety, load control, baggage, cargo and mail handling, aircraft movement control, aircraft loading, departure control systems etc. IATA delay codes are fully described in Airport Handling Manual 730. IATA has also published one code scheme in a form of a correlation table between IATA Delay Codes and ATFM delay codes used by Eurocontrol Central Flow Management Unit (CFMU) and this table now forms part of AHM 730 (see AHM 730 and Correlation between IATA Delay Codes and the CFMU Reasons for Regulation).
AIRPORT SLOT An airport slot is defined as the scheduled time of arrival or departure available for allocation by, or as allocated by, a coordinator for an aircraft movement on a specific date at a coordinated airport (Level 3 of Airport Activity). For scheduling purposes, the slot is the scheduled time of arrival or departure at the terminal, not the time of landing or takeoff from the runway (see IATA Worldwide Scheduling Guidelines Effective January 2010, 19th Edition). Airport slot is a time window of 30 minutes, starting 15 minutes before and ending 15 minutes after off/on block time. See the difference between Airport slot and ATFM slot, which are often confused.
ARRIVAL DELAY Arrival Delay is the difference between the Actual In and Scheduled Time of Arrival (ACTUAL IN - STA).
ATA Actual Time of Arrival: see Actual IN.
ATD Actual Time of Departure: see Actual OUT.
ATFM DELAY CFMU Air Traffic Flow and Capacity Management (ATFCM) departure delay is based on the difference between the planned off- block time and the calculated off-block time, taking into account slot time and estimated taxi time. It is rounded to whole minutes. ATFM delays can be attributed to the following IATA delay codes: 73, 81, 82, 83, 84, 87, 89 and 98. They are related to problems with weather, air traffic flow management restrictions, airport and governmental authorities and miscellaneous reasons causing a delay. See AHM 730 and Correlation between IATA Delay Codes and the CFMU Reasons for Regulation.
ATS Air Traffic Services are related to various flight information services, alerting services, air traffic advisory services and ATC services ∑ (ATD-STD) (area, approach and aerodrome control services). ifATD>STD ADMD= AVERAGE DELAY PER MOVEMENT ON ARRIVAL Number of Departures Average Delay per Movement on Arrival. Flights arriving ahead of schedule are considered delay neutral. The calculation is similar to that for ADMD
∑ (ATA-STA) ifATD>STD ADMA= Number of Arrivals
Planning for Delay: influence of flight scheduling on airline punctuality Trends in Air Traffic l Volume 7 103 AVERAGE DELAY PER MOVEMENT ON DEPARTURE Average Delay per Movement on Departure. Flights leaving ahead of schedule are considered delay neutral, so
∑ (ATD-STD) ifATD>STD ADMD= Number of Departures BLOCK TIME Time from departure from the gate to arrival at the next gate, either scheduled or actual.
BLOCK TIME OVERSHOOT (BTO) ∑ (ATA-STA) ifATD>STD Block Time Overshoot is the percentage of flightsADMA= with an actual block time which exceeds the scheduled block time (see section 5.1). Number of Arrivals CFMU Central Flow Management Unit is the operational unit of EUROCONTROL. Their mission is to enhance safety through co-ordi- nated management of the air traffic in Europe, to ensure congestion in the air does not occur and that available capacity is used effectively. www.cfmu.eurocontrol.int
CODA Central Office for Delay Analysis within EUROCONTROL. Its objective is to provide policy makers and managers of the ECAC Air Transport System with timely, consistent and comprehensive information on the air traffic delay situation in Europe, and to make these available to anyone with an interest in delay performance. www.eurocontrol.int/coda
COUNCIL REGULATION 95/93 see COUNCIL REGULATION 793/2004
COUNCIL REGULATION 793/2004 (previous COUNCIL REGULATION 95/93) On 21 April 2004 the European Parliament and the Council adopted Regulation (EC) No 793/2004 amending Council Regulation (EEC) No95/93 on common rules for the allocation of slots at Community airports. This regulation aims to stimulate a better use of scarce capacity at congested and coordinated Community airports. The EC slot regulation is mainly based on IATA guidelines (IATA Worldwide Scheduling Guidelines).
DELAY DIFFERENCE INDICATOR –FLIGHT (DDI-F) The punctuality at the end of the flight compared with the punctuality at the start of the phase expressed in minutes (see section 5.2).
DEPARTURE DELAY Departure delay is the difference between time of Actual Out and Scheduled Time of Departure.
DLY1, DLY2, DLY3, DLY4 and DLY5 IATA Delay Codes is a standardised list of two digit or corresponding two letter codes which airlines assign to delayed flights in departure. Airlines have the right to choose either to use two digits (taking values from 0 to 99) or two letters indicating exactly the same delay reason, i.e. delay reason due to bad weather on the destination station has a two digit code 72 which corresponds to the two letter code WT. Airlines usually keep a record of their five most penalising delay reasons and report them to CODA (Central Office for Delay Analysis) on a voluntary basis. In 2009 CODA had coverage of about 70% of all IFR flights in Europe.
ECAC European Civil Aviation Conference is an intergovernmental organisation which seeks to harmonise civil aviation policies and practices amongst its Member States and, at the same time, promote understanding on policy matters between its Member States and other parts of the world. www.ecac-ceac.org
104 Planning for Delay: influence of flight scheduling on airline punctuality Trends in Air Traffic l Volume 7 EET Estimated Elapsed Time. For IFR flights, it is the estimated time required from take-off to arrive at a designated point, defined by reference to navigation aids, from which it is intended that an instrument approach procedure will be commenced, or, if no navigation aid is associated with the destination aerodrome, to arrive over the destination aerodrome. For VFR flights, it is the estimated time required from take-off to arrive over the destination aerodrome.
EN-ROUTE Starts with the Take-off (OFF) and ends with the landing (ON).
EN-ROUTE DELAY En-route delay is the difference between time of Actual Flight Time and Planned Flight Time.
EUROCONTROL European Organisation for the Safety of Air Navigation is an international organisation whose goal is to develop, coordinate and plan for implementation of pan-European air traffic management strategies and their associated action plans in an effort involving national authorities, air navigation service providers, civil and military airspace users, airports, industry, professional organisations, and relevant European institutions. www.eurocontrol.int
EUROPE For the purpose of this study Europe is compromised of the 38 member states of EUROCONTROL: Albania, Armenia, Austria, Belgium, Bosnia and Herzegovina, Bulgaria, Croatia, Cyprus, Czech Republic, Denmark, Finland, France, Germany, Greece, Hungary, Ireland, Italy, Lithuania, Luxembourg, Malta, Moldova, Monaco, Montenegro, Netherlands, Norway, Poland, Portugal, Romania, Serbia, Slovakia, Slovenia, Spain, Sweden, Switzerland, The former Yugoslav Republic of Macedonia, Turkey, Ukraine and United Kingdom of Great Britain and Northern Ireland.
FLIGHT TYPE or ICAO FLIGHT TYPE Flight types. This information is taken from the flight plan field 8 (Flight Rules and Type of Flight). Flight types are classified in five categories (see ICAO Doc 4444):
S - Scheduled Air Service; N - Non-scheduled Air Transport Operation; G - General Aviation; M - Military; X - if the type of flight doesn’t match any of predefined categories.
FPL Flight Plan is a document prepared on the ground and carried by a flight crew prior to departure, giving information on depar- ture and arrival points, tracks, courses, IAS (indicated air speed) ground speeds, alternate airports in case of bad weather, type of flight, times and fuel for various legs, pilot’s name and number of people on board and other relevant data for the flight. In most countries, flight plans are required for flights under IFR. Under VFR, they are optional unless crossing national borders, however they are highly recommended, especially when flying over inhospitable areas, including water, as they provide a way of alerting rescuers if the flight is overdue. For IFR flights, flight plans are used by air traffic control to initiate tracking and routing services. For VFR flights, their only purpose is to provide necessary information should search and rescue operations be required. A structure with detailed explanation of each field of a flight plan is given in ICAO Doc 4444.
IATA International Air Transport Association is an international industry trade group of airlines with a mission to represent, lead, and serve the airline industry. www.iata.org
Planning for Delay: influence of flight scheduling on airline punctuality Trends in Air Traffic l Volume 7 105 IATA DELAY CODE IATA Delay Code is a standardised list of two digit or corresponding two letter codes which is recommended to airlines to use when assigning delay reasons for a flight with a departure delay. The list contains delay reasons marked either with numbers from 00 to 99, or with two letters (i.e. departure delay due to bad weather on departure station is marked either by the 71 digit code or by the WO letter code) which covers all possible reasons for delay: delays caused by passenger and baggage handling, delay caused by cargo and mail handling, delays caused by aircraft and ramp handling, technical delay reasons, delays which describe damage to aircraft and automated equipment failure, operations and crew caused delays, weather caused delays, air traffic control (ATC) restrictions and airport or governmental authorities caused delays, miscellaneous delays (see AHM 730 and Correlation between IATA Delay Codes and the CFMU Reasons for Regulation).
IATA WORLDWIDE SCHEDULING GUIDELINES The IATA Worldwide Scheduling Guidelines is a comprehensive set of procedures which are intended to provide guidance on managing the allocation of scarce resources at congested airports on a fair, transparent and non-discriminatory basis. It was developed by IATA for practical implementation of the EC Regulation 95/93 (see IATA Worldwide Scheduling Guidelines Effective January 2010, 19th Edition).
Recent IATA seasons:
W06 IATA winter season 2006 (from 29-10-2006 till 24-03-2007) S07 IATA summer season 2007 (from 25-03-2007 till 27-10-2007) W07 IATA winter season 2007 (from 28-10-2007 till 29-03-2008) S08 IATA summer season 2008 (from 30-03-2008 till 25-10-2008) W08 IATA winter season 2008 (from 26-10-2008 till 28-03-2009)
ICAO International Civil Aviation Organisation is a major agency of the United Nations, which codifies the principles and techniques of international air navigation and fosters the planning and development of international air transport to ensure safe and orderly growth. www.icao.int
IFR Instrumental Flight Rules General Air Traffic is a set of rules governing the procedures for conducting instrument flight.
LANDING This is the moment when an aircraft touched the ground for the first time and if it is recorded manually, it could also be the moment when an aircraft finished its landing on the runway, before leaving it.
LANDING DELAY Landing Delay is the difference between time of Actual On and Scheduled Landing Time.
LEVELS OF AIRPORT ACTIVITY Relating to the level of activity at an airports, there are three broad categories of airports:
Level 1 describes those airports whose capacities are adequate to meet the demands of users. Such airports are referred to as non-coordinated; Level 2 describes airports where, due to demand, a more formal level of co-operation and facilitation is required to avoid exceeding scheduling parameters. These airports are referred to as schedules facilitated; Level 3 describes those airports where demand exceeds the coordination parameters and voluntary cooperation to resolve the problems is no longer appropriate. In this scenario, formal procedures have been implemented at the airport to allocate capacity and coordinate schedules. Airports with such high levels of congestion are referred to as coordinated.
106 Planning for Delay: influence of flight scheduling on airline punctuality Trends in Air Traffic l Volume 7 OFF BLOCK This is the moment when a pilot released the brakes. Since pilots used to release brakes on their aircraft early to prevent delays from being recorded the new generation of ACARS has sensors which are able to recognise ground speed of more than three knots indicating aircraft movement. If the time is recorded manually, it could also be the moment when an aircraft left the gate.
ON BLOCK This is the moment when an aircraft arrived on a stand and when its ground speed is equal to zero.
OOOI Out/Off/On/In Times Data recorded by ACARS which correspond to push back from stand (Out), take-off (Off), landing (On), and on the stand (In).
PERCENTAGE OF ADVANCED FLIGHTS ON ARRIVAL The share of total flights arriving ahead of the Scheduled Time of Arrival. (PAF-A)
PERCENTAGE OF ADVANCED FLIGHTS ON DEPARTURE The share of total flights leaving ahead of the Scheduled Time of Departure. (PAF-D)
PERCENTAGE OF DELAYED FLIGHTS ON ARRIVAL The share of total flights arriving after the Scheduled Time of Arrival. (PDF-A)
PERCENTAGE OF DELAYED FLIGHTS ON DEPARTURE Percentage of Delayed Flights on Departure. The share of total flights departing after the Scheduled Time of Departure. (PDF-D)
PRC Performance Review Commission of EUROCONTROL was established to provide advice to the Governing Bodies of EUROCONTROL to ensure the effective management of the European Air Traffic Management System through a strong, transparent and independent performance review and target-setting system. PRC gives assistance to its Member States in setting targets as well as keeping care of performance review evolution and possible improvements. PRC is also responsible for proper functioning of PRU, its work programme and the quantity and quality of its output and the adoption of budgetary estimates relating to performance review to be included in the Agency’s draft budget. www.eurocontrol.int/prc
PRU The Performance Review Unit is responsible for monitoring and reviewing the performance of the European ATM System. As part of the EUROCONTROL Agency with the appropriate level of independence, the PRU supports the PRC. PRU does the analysis of ATM related performance parameters and based on this analysis gives recommendations for improvements to PRC. www.eurocontrol.int/prc
PUNCTUALITY In Europe, the percentage of flights departing within 15 minutes (=< 15’) of scheduled time of departure. The threshold criteria of 15 minutes may vary by carrier or region.
REACTIONARY DELAY Reactionary delay is a delay on an earlier flight leg of an aircraft which cannot be recovered during the turn-around phase. Reactionary delays use IATA delay codes 91 to 96. Reactionary delays may be rotational (IATA delay code 93) and non-rotational (IATA delay codes 91, 92, 94, 95 and 96).
STA Scheduled date and time of arrival, is the desired time that an aircraft should arrive at the gate at the airport of destination.
Planning for Delay: influence of flight scheduling on airline punctuality Trends in Air Traffic l Volume 7 107 STATFOR The Statistics and Forecast Service within EUROCONTROL provides statistics and forecasts on air traffic in Europe and monitors and analyses the evolution of the Air Transport Industry evolution. www.eurocontrol.int/statfor
STD Scheduled date and time of departure, the estimated time at which the aircraft will commence movement associated with departure.
TAFD Total Advanced Flights on Departure. Total count of flights where off-block time is greater or equal to five minutes prior to STD (Scheduled Time of Departure).
TAKEOFF Actual Take-Off Time (ACARS: OFF) is the moment when an aircraft took off from the ground and if it is recorded manually, it could also be the moment when an aircraft reached a certain height (e.g. 15m) or when it lined up for take-off.
TAKEOFF DELAY Take Off Delay is the difference between Actual and Planned Take Off Time.
TAXI-IN Starts with the landing (ON) and ends when the aircraft reaches the parking position (IN).
TAXI-IN DELAY Taxi In Delay is the difference between Actual and Planned Taxi In Time.
TAXI-OUT Starts when the aircraft leaves the parking position (OUT) and ends with the Take-off (OFF).
TAXI-OUT DELAY Taxi Out Delay is the difference between Actual and Planned Taxi Out Time.
UTC Coordinated Universal Time. All times in ATC are expressed in UTC unless otherwise stated.
VFR Visual Flight Rules are regulations which allow a pilot to operate an aircraft in good weather conditions allowing him to use the “see and avoid” method. Weather conditions must be better than VFR weather minimums in which case pilots are required to use IFR.
WAKE TURBULENCE CATEGORY Wake turbulence category L, M, H and J.
L- Shall be inserted for an aircraft with a maximum certified take off mass of 7000 kg or less, ex. Cessna 402 and 421; M- Shall be inserted for an aircraft with a maximum certified take off mass of less than 136000 kg but more than 7000 kg, ex. Boeing 727, Boeing 737, Airbus 320; H- Shall be inserted for an aircraft with a maximum certified take off mass of less than 560000kg but more than 136000 kg, ex. Boeing 747, Boeing 777, DC 10, Airbus 340; J- Shall be inserted for an aircraft with a maximum certified take off mass of 560000kg or more, ex. Airbus 380.
108 Planning for Delay: influence of flight scheduling on airline punctuality Trends in Air Traffic l Volume 7
For further information please contact
CODA, Central Office for Delay Analysis [email protected] www.eurocontrol.int/coda
EUROCONTROL
January 2010 - © European Organisation for the Safety of Air Navigation (EUROCONTROL)
This document is published by EUROCONTROL for information purposes. It may be copied in whole or in part, provided that EUROCONTROL is mentioned as the source and it is not used for commercial purposes (i.e. for financial gain).T he information in this document may not be modified without prior written permission from EUROCONTROL.
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