Collaborative project co-funded by the European Commission

Seventh Framework Programme

Aeronautics and Air Transport

FP7-(AAT)-2012-RTD-1

Theme [AAT.2012.7-26]

[Efficient Airports for Europe]

Project META-CDM

D.1.1– Workshop 1 Summary report

Aude Marzuoli, Isabelle Laplace, Eric Feron (ENAC)

Lynette Dray, Roger Gardner (University of Cambridge)

Thomas Günther, Gunnar Spies (BARCO Orthogon Gmbh)

Submission date: March 2013

Dissemination level: RE/PU/PP/CO

Change Log

Release	Date	Details of changes
0.1	2013-01-21	First draft
0.2	2013-01-29	Added summary of sessions 1 and 4 to chapters 2 and 5
0.3	2013-02-01	Added summary of session 5 and of collected questionnaires to chapter 6 and 8
0.4	2013-01-31	Added summary of session 2 and 3 to chapters 3 and 4.
0.5	2013-02-04	Added summary of of the Advisory Board discussions to chapter 7
0.6	2013-02-05	Work on document homogeneity (all pages)
1.0	2013-03-06	Finalised version 1.0
1.1	2013-03-24	Added hyperlinks

Table of contents

1 Introduction.. 4

2 Session 1 – MetaCDM Introduction.. 4

11:05-11:15 Workshop objectives and sessions, Thomas Günther (Barco Orthogon) 4

2.1 Fiona Hill (BAA) 4

2.2 Remy Denos. 4

2.3 Eric Feron (ENAC) & Lynette Dray (UCAM) 5

2.4 Thomas Guenther 5

3 Session 2 – Airport CDM: Current Challenges and Solutions. 5

3.1 Alison Bates. 5

3.2 Elisabeth Lagios. 5

3.3 Hervé Breton.. 5

4 Session 3 – Total Airport Management: The Next Step. 5

4.1 Yves Günther 5

4.2 Gero Hoppe. 5

4.3 Thomas Günther 5

5 Session 4 – Airports in the ATM Network: Collaborative Planning. 5

5.1 Ana Saez Sanchez (INECO) 5

5.2 Peter Foerster (DLR) 5

5.3 Olga Gluchshenko (DLR) 5

5.4 Marcel Richard (Eurocontrol) 5

5.5 Hamsa Balakrishnan (MIT) 5

6 Session 5 – Passenger-Centric CDM and Disruption Management: Future innovations 5

7.1. Gunnar Spies (Barco Orthogon) 5

7.2 Yu Zhang (University of South Florida) 5

7.3. Ifan Shepherd (Middlesex University London) 5

7.4. Aude Marzuoli (ENAC) 5

7 Advisory Board Meeting. 5

8 Workshop Questionnaires. 5

1 Introduction

The META-CDM (Multimodal, Efficient Transportation in Airports – Collaborative Decision Making) project aims to define the future of Airport Collaborative Decision Making – a future where the passenger becomes the center of attention. This project examines the coherence and co-ordination of the many systems that are part of delivering the traveler through an airport, primarily during disruptive events but also in everyday operation. This is done by considering both as well the airside and the landside CDM and their effectiveness. An additional dimension of this study is the analysis of the ability of alternative transport modes and communication to minimize personal disruption during crisis situations impacting air transport.

The Heathrow workshop on 15 and 16 January 2013 was the first Meta-CDM workshop of a series of three. The major objective of this workshop was to share knowledge of current airside and landside CDM initiatives and systems in Europe, the US and elsewhere to help identify strengths and weaknesses relative to crisis situations. In particular, this includes the comparison of the research & development (R&D) status and operational requirements in these domains.

For META-CDM, this will contribute to the development of roadmaps to

• determine how far available R&D results assist in plans to enhance operational practice and

• define future R&D work that contributes to efficient and intermodal transportation at airports, especially during highly disruptive events.

This report summarizes the workshop, including the accompanying advisory board meeting and the outcomes of questionnaires distributed at the workshop. An agenda is given in Appendix A, a list of participants in Appendix B.

2 Session 1 – MetaCDM Introduction

Agenda:

10:00-10:10 Welcome (Introduction/Agenda), Eric Feron, Roger Gardner (ENAC, UCAM)

10:10-10:30 Keynote Speech, Fiona Hill (LHR Airports Ltd)

10:30-10:45 Airport research in FP7, Rémy Denos (European Commission)

10:45-10:55 Objectives and partners of META-CDM, Eric Feron (ENAC)

10:55-11:05 META-CDM work packages, Lynnette Dray (Cambridge University)

11:05-11:15 Workshop objectives and sessions, Thomas Günther (Barco Orthogon)

Eric Feron and Roger Gardner started the first META-CDM workshop by welcoming attendees, thanking BAA our host and giving some logistic information.

2.1 Fiona Hill (BAA) (click here for presentation)

The keynote speech was then made by Fiona Hill from BAA who stressed what the META-CDM concept would mean for Heathrow airport:

- A real time and confirmed plain language across all key partners simultaneously to deal with current events, consequences, residual impacts or pre-determined prompts, alerts and solution sets;

- A way to inform the passenger in real time;

- A way to get data from external partners and to integrate them in the passenger journey so as to propose them solutions;

- A safe and intelligent pre-determined automated solution.

2.2 Remy Denos (click here for presentation)

Remy Denos (Dénos, Airport Research in FP7, 2013), the META-CDM project officer at the European Commission, then made a presentation of the various research projects on airports in FP7. He explained the context of the FP7 call “Efficient airports for Europe” in the scope of which the META-CDM project was selected:

- The 2010 volcano eruption which led to a closure of the European airspace between April 15 and 21 causing an unprecedented disruption of air traffic;

- Heavy snow falls which occurred in the past years such as for instance in December 2012 which led to flight cancellations and delays.

The main questions that such events give rise to include:

- What is the way forward for Airport-CDM ?

- What are the key technical solutions to develop ?

- How to connect with other modes ?

- How to set-up projects, in which frame ?

Are there needs for policy actions (e.g. Communication, Directive, Standards)

- How to finance ?

The META-CDM findings are therefore expected to provide some answers to these questions.

2.3 Eric Feron (ENAC) & Lynette Dray (UCAM) (click here for presentation)

The next presentation was made by Eric Feron from ENAC, who presented the objectives of the META-CDM project: “Defining the future of Airport Collaborative Decision Making – a future where the passenger becomes the center of attention - by examining the coherence and co-ordination of the many systems that are part of delivering the traveler through an airport, both in everyday operation and during disruptive events.”

The project breakdown in Work-packages was presented by Lynette Dray (Dray 2013) from the University of Cambridge. Figure 1 illustrates this project structure while Figure 2 presents the project timescale.

Figure 1 : META-CDM project structure (Dray 2013)

Figure 2 : META-CDM – Timescale (Dray 2013)

2.4 Thomas Guenther (click here for presentation)

The session 1 then ended with a presentation made by Thomas Günther (Günter 2013) from Barco Orthogon, who explained Key Focus Areas and Objectives of the project as illustrated in Figure 3 and who presented the agenda of this first META-CDM workshop (see Appendix A).

Figure 3 : META-CDM key Focus Areas and Objectives (Günter 2013)

3 Session 2 – Airport CDM: Current Challenges and Solutions

Agenda:

11:30-12:00 Heathrow A-CDM demonstration, Alison Bates (LHR Airports Ltd)

12:00-12:25 Airport CDM - Lessons learnt & challenges ahead, Elisabeth Lagios

12:25-12:50 A-CDM: Boosting the Airport turnaround process / Roissy CDG experience, Herve Breton (Thales)

3.1 Alison Bates

Alison Bates, on behalf of LHR Airports Ltd., began Session 2 with a live demonstration of the A-CDM tool that is used at Heathrow airport. This A-CDM tool keeps track of selected A-CDM milestones (estimates, targets and deviations) and allows different users after successful login to access information through its web interface. Further it provides various possibilities for post-ops analysis and statistics, including KPIs such as arrival / departure delay and punctuality. This A-CDM tool is used at Heathrow for common information sharing and includes some elements needed for Total Airport Management, but the tool is currently not connected to the CFMU.

3.2 Elisabeth Lagios (click here for presentation)

After the live demo Elisabeth Lagios presented “Airport CDM – Lessons learnt & challenges ahead”. She presented the history of A-CDM, its current status, lessons learnt and gave a future outlook. While CDM originated in the US, it became evident that it was not suited for the heterogeneous airspace of Europe. Thus in December 2001 the idea for Airport-CDM was born, although at this point in time the concept of A-CDM was still very vague and had to be defined within Eurocontrols’ A-CDM Task Force. First trials were made with Brussels airport and prototype developments with Barcelona airport. After about ten years the outcome was the A-CDM Implementation Manual, the Operational Concept Document (OCD) and the Functional Requirement Document (FRD). In parallel the EUROCAE WG-69 worked on a community specification on the minimum requirements for A-CDM which resulted in the documents ED-141, ED-145 and ED-146. These six documents are the basis for the standard ETSI EN 303 212 V1.1.1 which specifies the minimum requirements for A-CDM and is in force in all European member states. A-CDM is currently adopted in many states outside the European Union and is paradigm for an ICAO Global CDM Manual. Besides the few existing A-CDM airports at the moment, A-CDM projects are in execution at over 20 European airports, see Figure 4 for overview on A-CDM implementation status.

Figure 4: A-CDM Implementation Status (Lagios, 2013)

It can be expected that within the next years many of these airports will receive A-CDM status. The expected network effect of this is that ATFM slot compliance and therefore the efficiency of the Air Traffic Network especially under stress will increase significantly.

3.3 Hervé Breton (click here for presentation)

As last presenter in session 2 Hervé Breton presented “A-CDM: Boosting the Airport turnaround process / Roissy CDG experience”. CDG has been an A-CDM airport since 2010 and A-CDM projects are ongoing at Orly and Lyon. Hervé gave an overview about CDG Airport (incl. layout and statistics), the CDM program and stakeholders as well as the Collaborative Pre-Departure Sequencing (C-PDS) process, which is key element for providing TSAT/TTOT to the stakeholders at the airport and to the European ATM network. Important for the information sharing process at CDG are daily meetings of the main partners – ANSP, ADP, AFR and Météo France – to discuss the operations of the current day, see Figure 5. Frequent contributors are AOC (BAW, DLH, Emirates…), Fedex, Easy Jet, Singapore Airlines and other airlines.

$U:\90_Doc travail\CDM\Master ENAC\Collaborative information sharing.jpg$

Figure 5: Information sharing process at CDG (Breton 2013, courtesy of CDM@CDG)

Hervé presented various screenshots to explain the human machine interfaces (HMIs) that are provided to clearance delivery, apron control and tower in order to optimize the outbound process. Finally, the benefits of A-CDM at CDG were summarized. Typical KPIs used at CDG are TTOT quality, PDS delay, slot adherence and taxi time.

4 Session 3 – Total Airport Management: The Next Step

Agenda:

14:00-14:25 Total Airport Management - An evolutionary approach to managing an airport, Yves Günther (DLR)

14:25-14:50 Integrated “Air2Air Management” - Contributions to efficient and punctual airport operations, Gero Hoppe (Inform)

14:50-15:15 Flagship Project Total Airport Management Suite (TAMS) - Moving from concepts to reality, Thomas Günther (Barco Orthogon)

4.1 Yves Günther (click here for presentation)

The first presentation in session 3 was given by Yves Günther (German Aerospace Centre, DLR), with the title “Total Airport Management – An evolutionary approach to managing an airport”. Within his presentation, Yves gave the reasoning for the needs of, and an outlook on, Total Airport Management (TAM). He pointed out the difficulty of managing the many needed process steps performed by various stakeholders / companies to turn around a flight. Additional complexity is added by including the prediction of passenger movement (e.g. at check-in, before security etc.). But both, air- and landside processes need to be managed based on an agreed common setting of KPIs to align the sometimes deviating targets of the involved stakeholders / companies. The abstraction made through reducing the complex management of processes to a setting of flow and performance parameters (KPIs) helps the decision-makers in managing airport operations. How this might look like is shown by the photo in Figure 6. Yves pointed out that “mutual acceptance of a mandatory set of KPIs influences the operations of all the stakeholders”.

Figure 6: APOC environment at DLR in Brunswick (Y. Günther 2013)

Besides concepts for TAM, the recent work of the DLR included the implementation and validation of prototypes needed for the realization of TAM like the Total Operation Planer (TOP) and the PaxMan for monitoring and assessment of passenger processes and prediction of passengers‘ readiness. A simulator for an Airport Operation Centre (APOC) was set up in Brunswick to validate these and other tools connected to TAM in various test campaigns.

4.2 Gero Hoppe (click here for presentation)

Afterwards Gero Hoppe (Inform) presented “Integrated „Air2Air“ Management – Taking Aviation Management beyond CDM”. The presentation started with company introduction. This was followed by description of the motivation for an integrated air-to-air management and dependencies to be considered. Parts of the integration are the Turnaround Manager (TMAN), the Surface Manager (SMAN) and the Coupled Arrival and Departure Manager (AMAN/DMAN), Figure 7 visualizes the processes that were managed after the integration.

Figure 7: AIr2Air Steering (Hoppe 2013)

Gero gave an overview how these management tools work together and which process times (estimates, targets and actuals) are exchanged. He emphasized the process management capabilities of the Ground Star tool suite, especially that of its TMAN. An import additional element of this integration is the possibility for a joint what-if probing – the opening of an additional common context (copy) on all management tools that allows the probing of decisions before they are taken.

4.3 Thomas Günther (click here for presentation)

The last presentation in session 3 was given by Thomas Günther (Barco Orthogon) on the project “Total Airport Management Suite“, abbreviated TAMS. This German project was funded by the Federal Ministry for Economics and Technology and was comprised of the companies Siemens, Barco Orthogon, Inform, DLR, Airport Stuttgart and as associated partner ATRiCS. Target of TAMS was the implementation, simulation and validation of a suite of integrated systems to enable the overall TAM concept. This included ‘commercial off the shelf’ (COTS) products as well as innovative prototypes.

Thomas gave a company introduction. Barco Orthogon contributed their AMAN and DMAN as COTS products and developed as innovative prototype with the Airside Tactical Working Position (ATWP) the workspace for the ATC-Agent within an APOC. These tools were used to manage the runway and off-block (pre-departure) sequence in the TAMS project. The TAMS project included the landside, especially the prediction of the passenger movement within the terminal (i.e. DLR prototype PaxMan), which was discussed during the Q&A session. The developed tool suite was simulated and validated in various test campaigns at the Airport Control Centre Simulator (ACCES) of the DLR in Brunswick, Germany, see photo (Figure 8). More information is available on the TAMS website http://www.tams.aero/.

Figure 8: TAMS simulated in the ACCES of the DLR in Brunswick (TAMS Final Report, December 2012)

5 Session 4 – Airports in the ATM Network: Collaborative Planning

Agenda:

15:45-16:10 Turnaround Integration in Trajectory And Network (TITAN project), Ana Saez Sanchez (INECO)

16:10-16:20 Resilience of the future ATM system (Resilience2050 project), Peter Foerster (DLR)

16:20-16:35 Definitions of Disturbance, Resilience and Robustness in ATM Context, Olga Gluchshenko (DLR)

16:35-17:00 Time-line concept for Collaborative Workflow Management in dDCB, Marcel Richard (Eurocontrol)

17:00-17:25 Airport Surface Movement Optimization in the US, Hamsa Balakrishnan (MIT)

The session 4 focused on the presentations of projects dealing with collaborative planning between airports and the Air Traffic Management.

5.1 Ana Saez Sanchez (INECO) (click here for presentation)

Ana Saez (Sáez 2013) from INECO started this workshop session by presenting the TITAN project, a R&D project which belongs to the 7th FP. In a context of bottleneck at airports where departure delays are mainly due to the turnaround process, the objectives of the project are to:

- Increase Predictability: Reduce turnaround process std to 3 min;

- Reduce Operational Cost by 20%;

- Increase Efficiency of airlines’ operations;

- Reduce the total delayed flights (>15min) by 9%.

The aim of TITAN is to build a tool by using the methodology illustrated in Figure 9.

Figure 9 : TITAN methodology (source (Sáez 2013))

(summary)

The TITAN concept principles are:

- Integration with ATM Trajectory Based Operations

- Builds on A-CDM but goes further (e.g. better granularity)

- Net-centric and Trajectory Based Operations compatible

- Service oriented (a first in CDM)

- Looks at land-side also!

The TITAN tool aims at providing 5 services to the end-user applications which are the operational interface to external environments (Figure 10): passenger flow information service, baggage flow information service, Cargo/mail flow information service, aircraft status report service, airport information report service.

Figure 10 : TITAN services (Sáez 2013)

To validate the TITAN concept, detailed scenarios based on different airport configurations were run, modelling the various turnaround operations.

Figure 11 : TITAN parameters in scenarios (Sáez 2013)

Non-TITAN simulation scenarios (TITAN services disabled) as well as TITAN simulation scenarios (TITAN services enabled) were run showing a significant lower percentage of delayed sub-processes when using TITAN services.

Figure 12 : Percentage of delayed sub-processes for non-TITAN simulation scenarios and TITAN simulation scenarios (Sáez 2013)

ANA Saez concluded her presentation with a summary of the lesson learnt through the TITAN project:

- Encountered problems:

o SOA based systems not yet widespread in the airline and airport context (legacy environments)

o Existing systems able to receive TITAN information but providing information to TITAN may need workarounds

o Getting all the information TITAN needs may be a challenge and may prove expensive in some cases

- TITAN benefits:

o TITAN can be useful even at relatively simple airports

o New partners need special attention (data quality, security)

o Smooth integration with the business trajectory is possible (TITAN design)

o Passenger/baggage flow monitoring (including land-side/off-airport) at appropriate granularity needs to become standard (benefits go beyond TITAN)

o Transition needs good sales effort – otherwise not a major issue

o Engineering challenges relatively easy – institutional challenges can be showstoppers! This is true also for other projects!

5.2 Peter Foerster (DLR) (click here for presentation)

Peter Foester provided a short overview of the project RESILIENCE 2050. Resilience is a property of ecological, socio-ecological and socio-technical systems. The idea of the project is to apply resilience on ATM by:

- Developing new design principles to foster resilience for ATM, considering only physical and safety restrictions

- Validating the new concepts by the means of a simplified generic model that holistically provides the same level of detail

The RESILIENCE 2050 project is a FP7 project led by the Innaxis Research Institute and which started in summer 2012 for a three years duration. The project will be performed in 5 steps:

- Step1: ATM as a socio-technical system (Definition of Resilience, Description and abstraction of the interdependencies between the different stakeholders, Description of the impact of disturbances)

- Step 2: Data analysis (Searching for dependencies and resilient patterns within the current ATM system, How does the system cope with a specific type of disturbances?)

- Step3: Development of new design principles which enhance resilience (Mathematical representation of resilience by means of performance indicators)

- Step 4: Modeling of two systems (an Optimal model which is a highly optimized system and a Resilient model incorporating resilient design principles) by considering only physical and safety constraints and the same level of detail

- Step 5: Evaluating the benefit of the new design principles (On both systems, run of two scenarios (Undisturbed and disturbed scenarios) and use of perfomance indicators to analyse the results)

5.3 Olga Gluchshenko (DLR) (click here for presentation)

To illustrate the kind of methododology that will be used in the RESILIENCE project, Olga Gluchshenko presented the results of the DLR report named “Definitions of Disturbance, Resilience and Robustness in ATM Context”.

An extract of the abstract of this report is the following “The aim of this report is to give a short description of the developed framework, which incorporates created concept of robustness, resilience and relevant terms: disturbance, stress and perturbation. The created framework is illustrated with one simple example and is accomplished with an according decision-making chain. The report also suggests some qualitative and quantitative measures of resilience and robustness and provides a structured approach for investigation of these properties of a system. In spite of the fact, that the concept is developed in the ATM Context, it is transferable and can be used for any socio-technical system.”

One illustration of this report’s findings is provided by the Figure 13 when showing the decision-making chain leading to a new reference state after impacts of perturbations.

Figure 13 : Decision-making illustration (Gluchshenko 2012)

Other outputs are also for instance proposed ways to measures resilience and robustness of the system:

- Qualitiative measure of resilience comparing time of reaction with time of action;

- Quantitative measure of resilience such as the degree of recovery in a specified time or the overall time a system needs to come back to the reference state by transient perturbation;

- Quantitative measures of robustness such as the maximal “amount” of a disturbance quantified by frequency, intensity and duration, which can be absorbed by a system ( the system has no stress) or the minimal distance to the limits of robustness, where a system still has no stress,for a particular disturbance of some frequency, intensity and duration.

To summarize, the proposed steps for investigation of resilience and robustness of a system presented in this report are:

1. Define and describe the system and its boundary to the environment;

2. Specify the scale and the level of hierarchy to observe;

3. Specify performance parameters or indicators describing a state of the system;

4. Specify reference state of the system;

5. Classify disturbances by type, frequency, intensity and duration keeping in mind that the scale in which the system is defined and observed is a most important factor determining the level of detail required in characterizing disturbances and their impact on the system.

Olga concluded this presentation by stressing that if this concept is created in the ATM Context, it is transferable and can be used for any socio-technical system.

5.4 Marcel Richard (Eurocontrol) (click here for presentation)

Marcel Richard from Eurocontrol made a presentation on the Time-line concept for Collaborative Workflow Management in dynamic Demand Capacity Balancing (dDCB).

The dynamic DCB aims at replacing the current ATFCM and isolated FMP actions as illustrated in Figure 14.

Figure 14 : Dynamic DCB in Brief (RICHARD 2013)

The objective is therefore to build new concepts and procedures (Figure 15).

Figure 15 : dDCB process (RICHARD 2013)

This dDCB concept was applied on STAM scenarios. For instance, in case of move of an aircraft into a different scetor to that originally planned to solve a high-demand/workload issue, a new workflow was run as shown in Figure 16: after the identification of a short period of excessive demand/workload, a communication is intiated between the two flow managers and potential dDCB solutions are discussed. The optimised solution is confirmed by a DCB analysis to assess viability and, upon approval, communications with the relevant AOC’s commences. The implementation is then achieved when the dDCB plan has been agreed with the relevant ATC actors.

$C:\Users\oem\Dropbox\Heathrow presentation\Image4 scenario.png$

Figure 16 : Example of operational workflow with dDCB (RICHARD 2013)

5.5 Hamsa Balakrishnan (MIT) (click here for presentation)

Hamsa Balakrishnan from MIT made a presentation of US optimization research on airport surface movements.

The context of this research is the current airport surface inefficiencies due to airport congestion and leading to increased taxi times, fuel burn and emissions. Main research focus has been on departure metering which manages pushbacks during congested periods.

Table 1 summarises the different existing departure metering approaches.

Table 1 : Types of departure metering approaches (Balakrishnan 2013)

The pushback rate control is made in three succesive steps:

1. Formulating a dynamic control problem that recommends pushback rate to maintain departure throughput, given loading of taxiway and runway queues

2. Refining models using operational data by expressing the optimal pushback rate as a function of the queue length and by taking into account fleet mix, arrivals, etc to improve predictions of throughput to predict queue length

3. Implementing control strategy: the air traffic controller gets a pushback rate which is updated periodically (these pushback rates can be color-coded cards or a tablet display).

This approach was tested on Boston airport from August-September 2010 to July-August 2011 and resulted in:

- A total taxi-time saving of 16.7 hours in 2010 and 12.7 hours in 2011;

- 23-25 tons (6,600-7,300 gal) reduction in fuel burn;

- 52-58 kg decrease in fuel burn / gate-held flight;

- 71-79 tons CO2 reduction;

- Positive stakeholder feedbacks.

6 Session 5 – Passenger-Centric CDM and Disruption Management: Future innovations

Agenda:

09:30-09:55 The passenger within Performance Based Airport Operations, Gunnar Spies (Barco Orthogon)

09:55-10:20 Real-time Inter-modal Strategies for Airline Schedule Perturbation Recovery and Airport Congestion Mitigation under Collaborative Decision Making (CDM), Yuyu Zhang (Uni South Florida)

10:20-10:45 Virtual training for effective collaborative response to airport emergencies: The CRISIS Project, Ifan Shepherd (Middlesex University)

11:00-11:25 Existing work on collaborative decision making, disruption management and improving passengers' experience, Aude Marzuoli (ENAC / Georgia Tech)

7.1. Gunnar Spies (Barco Orthogon) (click here for presentation)

Gunnar Spies’ presentation focused on the passenger within Performance Based Airport Operations.

How can disruptive/crisis events seen from a passenger perspective be incorporated or be part of Performance Based Airport Operations (PBAO)?

Measures are needed to desribe and evaluate the performance of the whole journey (ground and air), as seen from the perspective of the passenger. Which existing measures are suited? Which new measures are needed? How can these measures be incorporated in PBAO?

Key Performance Areas and Focus Areas were derived in Episode 3 D2.0-03 - EP3 Performance Framework cycle 1:

• Capacity (Operational Performance): airspace, airport & network capacity

• Efficiency (Operational Performance): temporal, fuel & mission effectiveness

• Flexibility (Operational Performance): business trajectory update for scheduled and non scheduled flights, flexible access-on-demand for non-scheduled flights, service location flexibility, suitability for military requirements

• Predictability (Operational Performance): on-time operations, service disruption effects , knock-on effects

• Environment (Societal Outcome): Environmental constraint management, best ATM practice in environmental management, compliance with environmental rules, atmospheric Impacts, Noise Impacts

• Safety (Societal Out.): ATM-related safety outcome .

Key Performance Areas & Indicators detailed or added by TAMS project:

• Traffic Volume & Demand: handled traffic and handled passengers

• Capacity : airport declared capacity, slot compliance and terminal capacity

• Punctuality: arrival punctuality, departure punctuality, early arrivals, departure delay causes, waiting time at runway, boarding punctuality, passenger connectivity

• Efficiency: READY reaction time, aircraft stand & passenger gate freezing time, Level of Service (LoS)

• Predictability of : stand allocation accuracy: EIBT and EOBT, TOBT/TSAT Predictability to AOBT/ASAT, TOBT/TSAT predictability to EOBT, TTOT predictability, ELDT predictability, EPTG predictability

• Environment: noise / emission on ground, emission from ground vehicles, airport infrastructure energy efficiency

• Safety: number of aircraft queuing on sequence, number of safety incidents

• Security: number of security incidents.

Key Performance Indicators derived from ASSET

• Time: process time (POA) (duration, waiting time, service time), overall process time, walking time and transportation time

• Financials: fix costs, variable costs, investments, revenue

• Supporting parameters that were regarded as important to be assessed qualitatively are: space consumption, robustness, level of Service, security level, safety level, privacy constraints, compatibility, effort of implementation.

Evaluation of the presented Key Performance Indicators for META-CDM

The KPIs defined for PBAO so far are not focusing on the perspective of the passenger. The KPIs should be extended to include the whole travel (including non-air transport), e.g. how the airport is connected to public transportation:

• Airport shuttles, train to a major train station, etc.

• Reachability by car, parking lots, etc.

• Transfer time to/from the terminal, e.g. from parking.

META-CDM passenger focused Key Performance Areas/Key Performance Indicators:

• Accomplishment : pricing (Ticket, extra charges, shops, restaurants etc.), duration of whole travel (door to door), punctuality, Connectivity (& Is there a plan B?), compensation (Hotel, bus/train transfer, refund etc.)

• Comfort: accommodation (Seating, snacks, newspaper, etc.), Accommodation during disruptive events, Guidance (What to do next? Where to go? Etc.), reachability (transfer time, etc.), Waiting time (time wasted in queues etc.)

• Quality of Service (service personal): friendliness, communication (Language), courtesy / liability, reliability, timeliness of information, service time

• Safety: incident / accidents, health (e.g. contaminated cabin air ), security (e.g. risk of hi-jack, sky marshal )

• Trust / Image (Publicity & Experience): safety (Will I reach my destination alive?), service (Will the airline provide good service?), security (Will my personal data be treated confidentially?), connectivity (Will I reach my destination today?), timeliness (Will I arrive in time?), lugguage (Will it be lost / its transfer delayed?).

Influence of the passenger focused KPI on PBAO:

Passenger focused KPIs are mostly important for an airline, but some are also relevant for an airport as well.

– How is in general the connectivity at an airport during a certain time of the year?

– Will it be possible to catch an alternative mode of transportation?

– Is the site interesting (e.g. near to town), thus could I do anything interesting if my flight is cancelled?

Examples for derived research activities:

– Catalogue of critical times for air fare for each airport (to enable the airlines to make better recommendations for the passenger)

– Study on the weighting of paramenters to measure the performance from passengers´point of perspective

– Development of Passenger CDM (to put the passenger at the heart of PBAO).

7.2 Yu Zhang (University of South Florida) (click here for presentation)

Yu Zhang presented some results of her work on real-time intermodal strategies for airline schedule perturbation recovery and airport congestion mitigation under collaborative decision making.

Although there are different definitions about inter-modal transportation, a well-accepted one is “the concept of transporting passengers and freight on two or more different modes in such a way that all parts of the transportation process, including the exchange of information, are efficiently connected and coordinated.”Compared to freight or passenger transportation in EU, inter-modal in the U.S. is less developed. Freight inter-modality boomed up after introducing of containers. European has well developed public transportation system. The European air-rail inter-modal system features intercity rail stations on the lower levels of major airports. In the U.S., lagging infrastructure development holds back the possible coordination between air and rail modes. In long term, high speed train maybe necessary for certain areas, however, it requires massive capital investment and will encounter administrative and political barriers. Since curb access is possible without major facility investment, the cooperation between airlines and coach charter companies, however, is readily conceivable.

Enormous delays cost comes from airline schedule perturbations. There are different causes for the perturbations. Internally, mechanical failures, crew sick-off, crew strikes, etc. External reasons include adverse weather, a major reason caused airline delay and airport congestion, equipment outages at airports, terrorism threats, natural catastrophes. With the forecasted increasing demand, strategy office of FAA projected delays in 2014 and 2025 based on weather pattern of 2004. With doubled passenger traffic and possibly tripled aircraft operation in 2025, the delay will be 6 times of 2004 level. Bad days occur in summer and winter when there is more adverse weather. Aviation society is trying its best to accommodate increasing demand by constructing runways, develop new technologies. However, it is easy to notice that most delays are concentrated at hub airports where there is a space restriction for runway expansion. Also because the airspace around those airports is so busy, the marginal benefit of expanding airport capacity is limited. Furthermore, most delays occur in a few days when the situation is exceptionally severe. Considering these factors, there is an urgent need for some strategies that can be tactically implemented to reduce airline delay and airport congestion without utilizing airfield scarce resources.

Motivation-- Benefits of Substituting Ground Transportation Modes for Short-Haul Flights

There are nine large Hub airports in the US with ~15% short-haul flights within a 160-mi radius, and 26 metroplex systems in the US. The ideal strategies to be implemented now are these that do not need massive capital investment, do not need scarce airfield capacity and they have to be flexible enough to accommodate daily tactical operation.

The idea is to use real-time intermodalism in Passenger-Centric Recovery for Schedule Perturbation. In the case of a Hub-and-Spoke Network, short-haul flights would be substituted with ground transportation. In the case of a MetroPlex System, the options are to substitute short-haul flights, divert flights to alternative airport(s) and provide ground transportation between the hub and alternative hubs

A passenger-centric solution is based on information sharing and exchange among passengers, airports, air navigation service providers, and stakeholders of different transportation modes (air, rail, highway, public transit, for-hire vehicles, car rental agencies).

If airlines contract with local companies for motor coach service, the ability of such companies to respond in a timely manner to requests for service, which will be inherently urgent and unpredictable, will be critical. To assess this capability, internet sources were used to identify supply characteristics of local charter companies and a telephone survey was conducted to determine response time of charter companies to the type of urgent request that would arise with real-time inter-modal strategies. In addition, a sample of GDP logs was analyzed so that charter response time could be compared with the lead times that would be available to airlines making the requests.

The number of charter companies in six metropolitan regions offering different type of vehicles were investigated. The seating capacity of deluxe motor coaches ranges from 36 to 68 passengers. The motor coaches have shelf and belly space to accommodate luggage. Restrooms and air conditioning are standard equipment of the motor coach. It is also very common to have entertainment equipment such as TV/VCR. The number of companies which can provide executive coaches or limo buses were studied. In comparison to deluxe motor coaches, executive coaches and limo buses are characterized by plush perimeter seating, tables, TV monitors, and on-board concierge to serve drinks from the on-board bar. The unavailability or long lead time for some coach service companies to respond to urgent service requests are mainly caused by the lack of drivers.

According to the Ground Delay Program (GDP) experts at Metron, the GDPs with zero lead time occurred because airport weather conditions changed suddenly and the GDPs needed to be implemented right away. Negative GDP lead times resulted from the time lapse after a traffic specialist modeled the program but before it was sent out. Nevertheless, GDP specialists running the program have a “now_plus” parameter that they can set. By default, it is set to 45 minutes, which means that when a GDP is issued, flights within 45 minutes of departing are exempted. This policy recognizes that within 45 minutes of departure, passengers are probably already boarding. The GDP experts also noted that, while lead time is a good measure of how much notice the airlines received, airlines take actions during the course of GDP, even if it begins before they can have coach service in place. They also observed that GDPs—even those with little or no lead time according to the GDP logs—are not a total surprise to airlines because the likelihood of their occurrence at various airports is usually discussed on morning telephone conferences between the command center, traffic centers, and airlines. This is particular encouraging for the practicability of implementing real-time inter-modal strategies.

Study of Passenger Behavior under Stress and Uncertainty

In order to identify the appropriate Cognitive Load for Decision Making, the following steps are carried out :

• Design the presentation of reassignment options and determine how many options to be presented to passengers.

• The current approaches of measuring cognitive load falls into four categories that are the combination of two dimensions, objectivity (subjective or objective) and causal relation (direct or indirect).

• The dual-task method is a promising approach for direct measurement in working memory research, cognitive load research, and multimedia learning.

The following items are suggested for information Exchanges in Real-Time Intermodalism:

• Airports monitor the movement of passengers and give estimated information for passengers going through various key points.

• Within the passenger-centric architecture, an individual airline passenger database is needed to be shared with airport operators so they can obtain a precise estimate of passenger transit through critical spots of the terminal building, such as security checkpoints. These estimations, in turn, provide information to airlines on passenger progress towards take-off.

• The instrumentation needed for other modes of transportation includes real-time information about road traffic and the capacity of the railway system, public transit system, and hired vehicle companies.

• Some information is common— for instance, real-time travel time broadcast from Florida District 7 Traffic Management Center —but other information may not be easily accessible and will require negotiation among stakeholders to determining a sharing agreement and protocol.

• To build a real-time multimodal transportation network and provide recovery solutions for airlines and airports.

In current airside collaborative decision-making (CDM), airlines share with airport operators and air navigation service providers (ANSP) their flight schedules, flight plans, and operational decisions, such as cancellation of flights.

Mobile Sensors can represent opportunistic encounters, for instance with a smartphone App (Mobile Monitor) that scans the Bluetooth spectrum and writes down GPS coordinates and MACs seen @ timestamp.

Airline Perturbation Recovery with Responsive Passenger Reassignment

Solving the airline recovery problem with both distributed decision makers (passengers) and a centralized decision maker (airline) is an iterative process. While booking air tickets, passengers are asked if they would like to participate in the program and whether they are willing to reveal their locations before certain hours of their boarding time (e.g. 3 hours; airlines can trace their location with apps on passenger smart phones). During disruptive events, knowing the location of passengers and the availability of alternative transportation modes, as well as airport operation conditions and aircraft movements, airlines can offer passengers specific options of reassignment, either to later flights, to another airport in the same region, or to alternative transportation (it is possible to be indicated as virtual flights in airline system). Passengers select the options, and their responses are sent back to the airline. Airlines then can adjust their operational decisions accordingly. When in flight Wi-Fi becomes commonplace, this model can easily cover both passengers on and off flights.

With emerging technologies in the future, it can be foreseen that autonomous vehicles will be useful for Intermodal Connectivity. Autonomous vehicle ownership and scheduling could support the airlines, providing flexibility and ensuring passenger loyalty; the airports (new resource utilization, funding support, and facility development: loading and unloading area, baggage screening)

As a conclusion, real-time intermodalism provides a substitution of cancellation in airlines’ recovery, reducing the number of disrupted passengers, reducing the delay propagation to later flights and other parts of the network. Flight diversion reduces flight cancellation and works better under more severe capacity shortfall circumstances. Real-time intermodalism would improve the ability of emergency reaction of air transportation system. Furthermore, the design and implementation of proposed ideas need the wisdom of different entities with enhanced collaborative decision making platform.

7.3. Ifan Shepherd (Middlesex University London) (click here for presentation)

Ifan Shepherd is the Deputy Project Coordinator for another FP7 project, CRISIS, which has a goal to achieve better preparation of emergency managers and responders through interactive training simulations based on 3D videogame technology.

The project is interested in providing better preparation for major incidents or everyday accidents. CRISIS’s goals are to complement and enhance conventional training: classroom teaching, table-top exercises, role-play simulations, live exercises. It could be cheaper, offer more frequent/ad hoc/self service training, make it easier to replicate training setup and easier to apply controlled variations to training. CRISIS end-user partners are ANA Lisbon Airport – Portugal, ISAVIA Keflavik Airport - Iceland and the British Transport Police.

There are two team-training approaches. The first is trainer led [Fully implemented], where the trainer delivers the scenario, the emergency response team role plays, the operator manages the simulation software, the trainees are typically on one site and finally the trainer debriefs the trainees. CRISIS provides some important general characteristics, in particular:

Realism – physical & response fidelity, plausibility
Highly interactive environments
Real-time decision making
Two complementary perspectives.

The second team training approach is the two trainee perspectives. It focuses on field operations (FDX), first-person: immersive, first responders . The Command post (CPX) is a Third-person: Synoptic, commanders. This is closer to a field operations viewpoint. Some general characteristics of CRISIS are also highlighted:

Interaction and movement between the two during training sessions
Pre-prepared scenarios & injected events (VUF).

CRISIS offers several training approaches, based on 4C/ID model:

Training, demonstrating and testing
Repeat training (mastery) and varied training (transfer)
Part-task and whole-task training.

When it comes to understanding decision making, different information sources are available: published literature, airport emergency plans, interviews with end-user partners, observation of live training exercises. The design of CRISIS has to enable effective decision-making dynamics, in order to use CRISIS to evaluate virtual training.

Case study: Live exercise on 4-5 May 2012 -- major live exercise at Keflavik international airport, Iceland. The scenario consists in an aircraft crash landing and bursting into flames. It was NOT a training event, but a demonstration of competence in operationalising the Airport Emergency Plan (ICAO). It was preceded by table-top simulation exercise by team commanders on the previous day and involved some 200 personnel.

Day 1 focused on table-top exercise. A dozen key team leaders worked in the planning room for 2 hours around table-top airport map. There was radio communication with on-scene command centre. They were presented with the scenario at outset. Their interactions were closely observed and recorded. The usual team dynamics were present : dominant vs quiet individuals, talking vs thinking vs action taking and explicit vs implicit communication. The significance of the map and moveable ‘toys’ was noted: it was the focus of the interactions/discussions/debates, and the outcome/record of group decision making. On day 2 was the live exercise. There were scores of ‘actors’ role playing aircraft passengers (walking wounded, dead, unharmed, etc). All major emergency agencies were represented (fire, ambulance, police, hospitals, mountain rescue, trauma counsellors). Multiple communication systems were used: radio, cellphone, face-to-face, etc. The three major venues were the crash scene, the casualty treatment centre and the hospital (School).

CRISIS enables after-action review through different charts and displays, in particular a casualty flow plot, the records of the communications network, a timeline view of the decisions taken and topic maps summaries.

7.4. Aude Marzuoli (ENAC) (click here for presentation)

Aude Marzuoli provided a presentation on some key information obtained from the preliminary literature review for Meta-CDM.

Vision for Europe in 2050: "90% of travelers within Europe are able to complete their journey, door-to-door within 4 hours. Passengers and freight are able to transfer seamlessly between transport modes to reach the final destination smoothly, predictably and on-time." This is the European Commission goal from Flightpath 2050.

The objectives of META-CDM are to study the conditions under which Collaborative Decision Making can help the transportation system deal with major disruptive events as they affect civil aviation and facilitate the passenger's journey.

The Air Transportation Network is a dynamic network, where connections appear and disappear. Airports in close vicinity tend to have collaborative rather than competing effect on air passenger demand. The networks in Europe/ China /US are fairly different: which network provides the best service to the passengers? Europe has the highest percentage of destinations, but connections take longer than in the US or China. Each country favors connectivity towards its own airports. There is better coordination in the US but secondary airports have been marginalized.

Delay Propagation and Performance in the Air Transportation System

A total of 103 million system delay minutes cost $7.7 billions to scheduled U.S. passenger airlines in 2010. In Europe, reactionary delays add up to half of the delay minutes. Metrics have been developed to quantify the propagation of delay in the network: magnitude, severity, depth, depth ratio, stay, crew out, split . Propagated delays create significantly more impact than the original root delays themselves. A single delay can "snowball" through the entire network. Keeping aircraft and crews together can help to mitigate the impact of disruptions. Delays that occur early in the day can cause greater propagation than delays later in the day.

Flight cancellations correspond to less than 3% of domestic flights, and are therefore hard to predict. An analysis of cancellation factors can lead to cancellation prediction, to estimate reduction in flight delays due to cancellations.

The quantification of interdependencies between airports can help investigate delay propagation. The main causes of delays are queues and weather. For instance, Washington-Baltimore, New York and South Florida have huge impacts on the delays in the US. There is a need for proper regional airport level and airspace planning.

Collaborative Decision Making

An airport in Europe is considered a CDM airport when A-CDM Information Sharing, Turn-Around Process and Variable Taxi Time Calculation concept elements are applied at the airport. A key aspect of the CDM effort is its reliance on data analysis and objective critique.

Disruptions in Air Traffic and on the Ground

The different mechanisms of airline schedule recovery in case of disruption: aircraft swaps, flight cancellations, crew swaps, reserve crews and passenger rebooking. The problem is usually solved in a sequential manner: infeasibility of the aircraft schedule, crewing problems, ground problems , and at last the impact on passengers.

Vaze evaluated the congestion impacts on the NAS stakeholders while explicitly accounting for their interactions and proposed congestion mitigation mechanisms that are beneficial to these different stakeholders: administrative slot control, congestion pricing, airport slots auction. At the current level of passenger demand, delays are avoidable to a large extent by controlling the negative effects of competitive airline scheduling practices. The level of congestion in a system of competing airlines is an increasing function of the number of competing airlines, a measure of the gross profit margin and the frequency sensitivity of passenger demand.

Multi-modal Transportation

The volcanic eruption in 2010 also had knock-on effects on other modes of transportation, because of the rigidity and complexity of transport networks, and the lack of appropriate preparation.

The partial substitution of some short-haul flights with High Speed Rail transport, either through modal competition or complementarity, is already in place in four European hubs (Frankfurt Main, Paris CDG, Madrid Barajas, Amsterdam Schipol). The High Speed Rail substitutive capacity does not act as a barrier to developing air/rail substitutions at the airport. Even very modest substitution of up to 2% air passenger short-haul flights with the equivalent high speed rail services may produce substantive savings, up to about 20% in airline and air passenger delays and up to 17% in related costs.

For the passenger, traveling across several modes of transportation to complete their journey can be difficult, especially when it comes to planning travel times. To improve the passenger's experience, more and more advanced transport information systems (ATIS) provide services such as route planning, navigation, updates on disruptions, real time information alerts. A multi-modal supernetwork encompasses:

– road, rail, air, water transportation .

– private (e.g. foot, bike, car) or public modes (e.g. bus, train, tram, metro).

– the switch between modes occurs only when the transfer is possible. Some links are time independent, others time dependent or stochastic time dependent.

– travel time and monetary cost need to be computed.

Reliability of the schedule in a multi-modal trip is essential. The traveling time in each mode and the waiting times in between should be balanced to improve passengers' experience.

Shifting the focus towards the Passenger

Flight delays do not accurately reflect the delays imposed upon passengers' full multi-modal itinerary. The growing interest to measure ATM performance calls for associated metrics, reflecting the passenger's experience. Propagation-centric and passenger-centric performance metrics differ from existing classical metrics, with regard to intelligibility, sensitivity and consistency. Computing passenger delay using monthly data from a major airline operating a hub-and-spoke network shows that disrupted passengers, whose journey was interrupted by a capacity reduction, are only 3% of the total passengers, but suffer 39% of the total passenger delay.

Some major findings on 1,030 routes between the 35 busiest airports in the US in 2006 are as follow:

– High passenger trip delays are disproportionately generated by canceled flights and missed connections.

– Trend analysis for passenger trip delays from 2000 to 2006 shows the increase in flight operations slowed down in 2006, while enplanements kept increasing, due to a continuous increase in load factor. Passenger performance is very sensitive to changes in flight operations, with an increase in annual total passenger trip delay in 2006, while flight operations barely grew.

– 17% of routes generate 50% of total passenger trip delays. 9 of the busiest 35 airports generate 50 % of the total passenger trip delays.

– Congestion flight delay, load factor, flight cancellation time and airline cooperation policy are the most significant factors affecting total passenger trip delay.

Understanding the passengers' preferences is essential in a period of multi-airports regions' growth and intense competition between airlines, whether legacy airlines or low-cost. To model the airport choice of air travelers between 4 airports in Hing-Kong Delta region, and describe scenarios of regional airport competition and airport coordination, Loo includes: average propensity to travel, spatial distribution of air travelers, regional inflows and outflows of passengers, ground transportation infrastructure capacities, number and physical location of airports, ground transportation cost, congestion effect, cross-border cost, airport Level Of Service (LOS) and government's aviation policy. How do passengers choose an airport over another within the same multi-airport region? Air fare, access time, flight frequency and the number of airlines are all decision-making factors. The number of airport access modes, access cost, airport shopping area and queue time at check-in counters are not significant.

Results of DGAC (Direction Nationale de l’Aviation Civile) study on 49054 air passengers 2011 in France: 80 % of passengers only take one flight. A passenger needs on average 71 minutes to reach the airport. 83% of passengers bought a ticket by itself, not within a full package, on average 52 days before departure. 83% had electronic tickets. 59% had non refundable tickets, 23% did not know if their ticket was refundable. 51% had non exchangeable tickets, 26% did not know. Why did some passengers have a connection in France? 63% said there was no direct flight to their destination, 19% say it was cheaper this way, 9% said because the schedule matched their needs better, 9% said someone else booked their ticket.

31% of passengers without a connection take public transportation to get to the airport. 30% of passengers were dropped off by someone with a car, 18% by a cab. Why don’t they use public transportation? 23% felt more free with a cab or a car, 21% said the public transport schedules did not meet their needs, 20% complained that the public transport options took too long, 17% thought it was not convenient (heavy luggage), 12% explained they would have had too many changes to make.

7 Advisory Board Meeting

The first meeting of the META-CDM Advisory Board (AB) followed on from the workshop. Attendees were the appointed external Advisory Board members (Elizabeth Lagios, Hamsa Balakrishnan, William Swan, Herve Breton, Louise Pengelly, Marcel Richard) the EU Project Officer (Remy Denos) and members of the MetaCDM project team.

The EC Project Officer, Remy Denos set the scene for the AB with some advice and observations as follows:

· It was important to avoid duplication of work with other projects yet equally MetaCDM should draw upon results of the Resilience 2050 project and from connections with ModAir;

· Innovation was a key ingredient and the passenger perspective should be advanced, including exploring ways to engage with the passenger, e.g. with the provision of data to the CDM system;

· Testing the developing options for real-world feasibility was essential so that industry ‘bought in’ and could accept cost and practical implications of a broader CDM system;

· Cognisance should be taken of regulatory, passenger rights and other constraints as options evolved;

· Examining where bottlenecks existed and unpacking those should be a significant theme of the work;

· The target audience for the project should be defined early, including the level of that audience and the best to communicate outcomes;

· After this first information sharing stage, the next AB should review working plans going forward and proposals towards the concept stage.

Broadening the dialogue, there followed a discussion about engagement with stakeholders. SESAR was clearly an essential partner but also it was appropriate to talk with passenger representative organisations and a visit to the Amadeus group was recommended. Mapping the stakeholder interests and groups would be helpful but expectation management was also important as the project was focused at the strategic and concept level. Whilst MetaCDM might be expected to lead to more detailed analysis, this would not be undertaken within the project.

MetaCDM should avoid too much exploration or analysis in the airside CDM area as this was already being addressed through SESAR and a number of projects though it was appropriate to use airport knowledge and expertise to make the right connections (from airside to landside) and access key contacts. From this discussion a few key issues arose for attention:

· clarity over the focus of MetaCDM and whether it was looking at forestalling/preventing crisis events, managing them or recovering from them. The clear preference was for the airports was for it to be recovery;

· exploring the difference between how CDM is system focused (where the aircraft is almost a surrogate for the passenger) and the passenger dynamic. Whilst a concept that is passenger centric was useful, it was important to explore how airports could improve working with stakeholders to solve problems, e.g. when the ash cloud struck Europe, why did passengers stay at airports and what role did insurance terms have upon attitudes? Widening the dialogue to include such stakeholders was important;

· unpacking the ‘command and control’ approach of a centralized system reliant upon decision-makers versus a move towards greater ‘informed autonomy’ that might allow for more dynamic responses and prevent the passenger getting caught up in the system;

· it was important to cover both CDM crisis practice and system resilience in discussions with airports and other stakeholders;

· approaches used in analogue industries would be useful to learn.

It was acknowledged that there were significantly different issues regarding crisis CDM at capacity constrained versus non-capacity constrained airports. Snow/ice problems at Heathrow (running at 99% of capacity) illustrated the very thin tolerance to disruption and how that can cascade. Various Heathrow de-icing studies have been undertaken and these might be of assistance. It was important to look at a range of representative airports, to cater for systemic disruption, but focus on those key hubs where impacts would be most felt.

Breaking the crisis CDM problem down was key to getting the questionnaires and surveys right and thus likely to generate useful data and information. Information gathering should be from airlines (network level downwards), emergency services, insurers, ground transportation providers and hotels. Another community to engage with would be the media and how they dealt with crisis events and how communication could be improved.

It was agreed that the next Advisory Board meeting should examine the project plan and the steps towards a concept.

8 Workshop Questionnaires

Stakeholder input is vital to MetaCDM. To help gather information from those attending, questionnaires were distributed to attendees to fill in during the course of the workshop, with a selection of questions on subjects related to the MetaCDM brief. The purpose of the questionnaires was to help provide extra data to assist the early stages of the MetaCDM project: for example, which types and sources of disruption we should be focusing on, which system bottlenecks are most important, and which technologies to overcome these bottlenecks should be investigated by the project. 13 responses were received, with most respondents answering all questions.

A summary of comments by question is given below.

What are the most important sources of disruption at airports?

a) What are they now?

Most answers concentrated on natural events as a major source of disruption – particularly weather (11), and especially convective/extreme weather. Examples included snow, fog, thunderstorms and hurricanes, depending on airport location. Other unexpected natural events (e.g. volcanic ash, pandemics) were also noted (4).

Disruption from within the aviation system was also highlighted. Mechanicals, high airport utilisation (90-100% of capacity), runway closure, turnaround, lost passengers, misunderstandings with information, sensitive information, and inefficient management resulting in sub-optimal throughput were noted as potential sources of disrupted operations. Irregular operations themselves, including service delays, diversions, late arrival and congestion were noted by 2 respondents; although these irregular options may stem from the other sources of disruption considered, they can themselves be the cause of further (propagated) disruption.

Accidents and incidents, both at the airport and on route to and from the airport, were also covered. These included crashes, aircraft accidents and incidents on maneuvering areas and aprons (3), as well as service disruption with reduced transport links to the airport. Terrorist attacks and security threats are another source of potentially major disruption. Another weakness highlighted was IT systems – either via systems failure or cyber attack (2 responses).

Finally, strikes/industrial action were mentioned by 3 respondents.

b) How will that change towards 2050?

Two major strands here were climate change-induced increases in the frequency and severity of weather events (3), and increased demand in the aviation system leading to more airports operating at capacity (4). In the former case, respondents also noted that weather prediction systems may improve, leading to increased weather predictability, and that airframes will be more resistant to weather perturbation. Mitigation measures to deal with weather impact were also noted as a likely future development. It was also noted from a UK perspective that without runway capacity resilience in the South-East, or legislation to prevent strikes, the only areas realistically controllable into the future are IT and equipment to mitigate poor weather.

In the latter case, reductions in airport capacity/headroom will reduce airport resilience and ability to recover from disruption (no firebreaks) and lead to increased congestion and delay, with more constrained airports.

Future changes may also be expected in technology and ability to share information. In particular, policies and regulations regarding confidential information may change. In addition, one respondent considered that most sources of disruption are likely to continue unchanged from the present day.

Obstacles to optimal airport crisis management – what are the major system bottlenecks?

A mix of perspectives was given here: some responses were from the point of view of the passenger, and some from the point of view of the crisis response team, with a number of obstacles relevant to both experiences.

From the passenger’s perspective, security (2), immigration/passport control (2), staffing levels, and informing passengers about the status of their flights, and the expected actions resulting (new flight time; transfer to another mode of transport etc.) were highlighted.

From the point of view of crisis response, the major problem highlighted was lack of or poor information sharing and collaboration, and lack of communication between stakeholders (7). Similarly, some respondents criticised current crisis response for a lack of preparation and holistic planning involving all stakeholders. The different incentives between stakeholders (e.g. passengers, airlines, ATC, airports) were noted, as well as difficulties arising from the large number of parties involved in crisis response and the need to make early warning available to all stakeholders. One respondent noted that regional crises require regional decision making, which is usually not in place.

Institutional barriers, including a reluctance to use the latest technologies which can help (e.g. GPS, PBN etc.) and safety standards that do not incorporate/reflect the benefits of the latest technologies and practices were also noted, as were pride, power and territorial issues, including greed about high fare passengers. The issue of confidential and/or sensitive information was also brought up by one respondent, who noted that if we could share all information (e.g. SWIM) then management would be better.

Current infrastructure was another obstacle to crisis management highlighted. Two respondents mentioned runway capacity, and how that capacity is used. Access to the airport, and runway/taxiway congestion, were also mentioned.

Greater integration of ground transport providers in airport crisis management:

a) What are the major challenges?

A wide range of challenges were mentioned here. One major concern was passenger acceptability (3) and the difficulty of keeping the same level of service for the customer (both passengers and freight) – particularly when passengers are individuals who may have widely differing needs.

Information sharing was also seen as a potential problem with several different dimensions. These include getting information to passengers, sharing information between stakeholders (passenger, road, bus, train, traffic jams etc. through the same system, and knowing what passengers do when they leave the airport on the ground. The importance of mitigating the decision load when providing information on alternative transport options to already-stressed passengers was highlighted by one respondent, who suggested providing (roughly) equivalent mixes of transportation access at all major airports. Another problem for information sharing is the need to have accurate sources of information, including accurate forecasts of disruption.

Similarly, coordination of ground transport may cause difficulties. The need for common crisis planning between airlines, airport and the local/extended area public transport system was highlighted by 2 respondents. Problems may arise in efficiently engaging ground transportation, including the issue of providing enough equipment, where the equipment may be expensive and companies do not necessarily have lots of available capacity. The interoperability of air and ground transport systems, and determining relevant events that can inform good decision making using them, were also highlighted, as was the problem of finding a solution algorithm to make airline operations work optimally with the new layer of complexity. The need to provide new infrastructure or adapt older infrastructure to enhance the connectivity between different modes was noted by 2 respondents

Acceptability to transport providers (both airlines and ground transport) was also highlighted as a problem by several respondents. Competition and commercial sensitivities were seen as a potential barrier, as was maintaining a sustainable cost of air transport in a multimodal transport model.

One respondent noted that the benefits of integrating ground and air transportation were unclear, and that arrivals integration would be easier and clearer to see benefits from (e.g. matching the passenger arrival flow with availability of taxis/trains), as the landside system is more random/unpredictable than the airside.

b) Is it a worthwhile goal to try and achieve greater integration?

11 respondents answered yes (with the corollaries that it must be for the passengers’ benefit; that the benefits need to be proven; ‘I speak as a frequently frustrated air traveller’; this would certainly improve passenger satisfaction). One respondent considered it a partially worthwhile goal, more likely achievable at newly constructed airports in their planning phase. The final respondent left this question blank.

Which ideas, CDM concepts and CDM-enabling technologies should be investigated?

a) Existing ideas, concepts and technologies

Various already implemented A-CDM concepts were mentioned by 2 respondents: AMANs, DMANs, integrated AMAN-DMAN, and other managers for surface movements and turnaround. TAMs were mentioned by 2 respondents, with one noting that the project should explore multiple TAM approaches. Other concepts mentioned included information sharing, a synthetic view of information per actor, ground-air CDM integration, providing an interface between all players (ground handling, passport control, transport providers etc.), the provision of information and solutions to the passenger, interoperability between local and network systems, punctuality, economics and operations (capacity), crisis-focused research into team-based collaborative decision making, split approaches (one for everyday disruption, one for crises) and approaches to sharing and managing information when some of it is private or confidential.

One respondent commented that though existing ideas are already good, more focus is needed to drive implementation at airports. Another commented that the MetaCDM project should collect hub airport-public transport organisation and initiatives; a further suggested project direction was to investigate how to enhance the Information System platform to include the necessary information for enhanced CDM.

b) New ideas, concepts and technologies

TAMs were also mentioned in this section by one respondent (here including the turnaround process). Other technological concepts mentioned included real-time data collection and information distribution, terminal processes managers, integration between terminal and airfield managers, ground transportation managers, service orientation, and the work of the TITAN project. One respondent commented that we should explore different CDMs in general.

Ground transportation technologies suggested for investigation included ITS and individual car transport information possibilities related to congested routes at the arrival airport. One respondent noted that the project should explore multimodal transportation which keeps the level of service to the customer at current levels. Another commented that energy options are likely to rapidly evolve in the near future.

Passenger-related concepts included the use of mobile phones to (voluntarily) track passengers, making more options available to passengers with data, understanding passenger behaviour and including passenger perception/soft factors on top of ‘hard’ system CDM factors.

More research-based concepts included the idea of multi-modal network modelling and analysis, and investigating what the limits and negative consequences of group-based sense-making and decision-making are.

What are the main current systems/process deficiencies?

The most-mentioned systems deficiencies were to do with data sharing (4). Respondents commented that too much data was still not shared, was incomplete or fragmented or was only obtainable from different sources. One data source specifically mentioned as lacking was information on passenger flows (e.g. connecting to other flights). Another respondent noted that a consolidated information overview is needed. Similarly, another respondent suggested that the ability to provide a holistic view of everyone’s response plans and share that information in real time is needed. However, one respondent commented that (most of) the information and systems to use it are already available (wifi, bluetooth etc.); the main problem being that we don’t know how to use it – i.e. that processing information is the problem, but more information itself is not needed.

A lack of passenger data collection was also highlighted by two respondents – specifically ‘timestamp’ data (knowing where passengers are at any given time). One respondent also noted that passenger needs and satisfaction need to have a higher priority in crisis planning.

Weak collaboration between modes was discussed by two respondents. The problem of a lack of interest in collaboration between modes due to lack of understanding of potential gains (where all collaborators suffer if one does not fully cooperate) was also mentioned. Two respondents highlighted the current lack of connections between different modes as a problem, particularly in regard to connecting public transport to the landside. A lack of protocols to respond to crisis collaboratively for different modes was also noted.

The other responses addressed modelling, prediction and the distinction between different types of response. One respondent noted that systems haven’t yet satisfactorily incorporated weather models to look ahead and predict disruptions/preventative measures to take. Another noted that crisis systems are different from disruption systems and require different responses. A third noted that current models are incomplete, and a fourth noted that the project should address real systems and derive process deficiencies from their experiences. Finally, one respondent commented that they needed to know what the system end-state is to answer this question.

Which KPIs are missing to measure the performance seen from the passenger’s point of view (customer satisfaction?)

Many respondents highlighted measures relating to a passenger’s door-to-door journey. These included door-to-door travel time/ door-to-door efficiency (3), passenger delay, arrival times and punctuality as opposed to aircraft delay (2), and the on-time arrival of passengers at their final destination with their luggage (the final destination being e.g. a hotel in a meeting location). Passenger costs were also mentioned (2), including a passenger value of time (accounting for buffer time) and a higher value of delayed time (approximately 3 times higher). Overall satisfaction, as a measure of to what extent the expectations of the passenger are met, was another suggested KPI, as were repeat business and customer complaints. Another respondent suggested customer satisfaction and KPIs mitigated by cost (e.g. to find the optimum points in a 3-D service delay, customer satisfaction and cost space). The incidence of passenger troubles during the trip (change of terminal, of airport, having to collect and re-register luggage) was also suggested. Two respondents suggested the weighting of delays by perception, as not all delays are perceived equally (e.g. waiting on the tarmac ‘feels’ longer than a longer flight time, queuing at the end of the runway could feel longer than a gate delay; passengers have different perceptions of travel time to the airport and processing time to reach the airplane when travelling from small and large airports, so that 1.5 hours would be acceptable at LHR and very unsatisfactory at BEG). One respondent suggested the project could learn a great deal from recent theories and empirical research on trust, loyalty, and experiential marketing – as modern marketing is hugely customer focused rather than product or supplier focused. Finally, some airport ease-of-use KPIs were suggested: ease of orientation at the airport, ease of vehicle parking at the airport, and Increased use of biometric technologies at immigration and customs.

9 Final Remarks

The META-CDM team received positive feedbacks on the first META-CDM workshop, from attendees of this event.

They stressed their interest in the project and helped to identify important issues that the project has to solve:

· clarifying if the focus of the project is to look at forestalling/preventing crisis events, manage them or recover from them;

· exploring how airports could improve working with stakeholders to solve problems, e.g. when the ash cloud struck Europe, why did passengers stay at airports and what role did insurance terms have upon attitudes? Widening the dialogue to include such stakeholders is important;

· moving towards greater ‘informed autonomy’ that might allow for more dynamic responses and prevent the passenger getting caught up in the system;

· covering both CDM crisis practice and system resilience in discussions with airports and other stakeholders.

Bibliography

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Breton, H., & Rivoisy, F.-X. (2013, January). A-CDM: boosting the airport turnaround process. Presentation for the first META-CDM workshop. London Heathrow.

Dénos, R. (2013, January). Airport Research in FP7. Presentation for the first META-CDM workshop. London Heathrow.

Dénos, R. (2013, January). Review report META-CDM. London Heathrow.

Dray, L. (2013, January). META-CDM workpackages. Presentation for the first META-CDM workshop. London Heathrow.

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OTHER GUESTS
Antony Evans	City University London
Choy Dawen	Changi Airport Group
Chua Kwee Hong	Changi Airport Group
Andrew Cook	University of Westminster
Wade Stanfield	Thales ATM
Simon Brown	NATS
Gregor Weil	Lufthansa
Fiona Hill	BAA Heathrow
Alison Bates	BAA Heathrow
Philippe Jasselin	Thales Air Systems
Ladislav Cermak	Air Navigation Services of the Czech Republic
Jean-François Perelgritz	EADS Innovation Works
Florian Piekert	DLR
Bojana Mirkovic	University of Belgrade
Terry Russell	Department for Transport
Nickie Dean	BAA Heathrow
Richard Mills	Boeing
Mike Price	London Borough of Hillingdon
Andreas Schäfer	City University London
Axel Classen	DLR
David Esteban Campillo	Boeing Research & Technology Europe

CONSORTIUM
Eric Feron	ENAC
Aude Marzuoli	ENAC
Amedeo Odoni	MIT
Georges Mykoniatis	ENAC
Daniel Delahaye	ENAC
Sonia Cafieri	ENAC
Yohann Brenier	ENAC
Isabelle Laplace	ENAC
Thomas Günther	BARCO
Gunnar Spies	BARCO
Roger Gardner	Cambridge University
Lynnette Dray	Cambridge University

SPEAKERS AND ADVISORY BOARD
Rémy Denos	European Commission
Marcel Richard	Eurocontrol
Peter Förster	DLR
Olga Gluchshenko	DLR
Gero Hoppe	Inform GmbH
Yves Guenther	DLR
Ana C. Saez Sanchez	INECO
Ifan D. H. Shepherd	Middlesex University Business School
Elizabeth Lagios	Senior CDM Consultant
Yu Zhang	University of South Florida
Herve Breton	Thales
Hamsa Balakrishnan	MIT
Louise Pengally	BAA Heathrow
Francois-Xavier Rivoisy	Aeroports de Paris
William M. Swan	Seabury Airline Planning Group