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FDM Raw Data: Why Binary Data and How to Decode It?

Authors: Lukas Hahndorf & Javensius Sembiring (TU Munich)

SafeClouds.eu gathers 16 partners for research collaboration with a wide and diverse group of users, including air navigation services providers, airlines and safety agencies. SafeClouds.eu encourages active involvement from users, as the project aims to apply data science techniques to improve aviation safety. SafeClouds.eu is unique as it involves data combination and collaboration from ANSPs, airlines and authorities in order to improve our knowledge on safety risks, all while maintaining the confidentiality of the data. This safety analysis requires comprehensive understanding of various data sources, and supports the use case analysis as selected by the users.
The basics of the FDM data, as one of the main data sources for the project, is outlined in this post.

Onboard Recording

A large amount of data is recorded during civil aircraft flights. Apart from the “Flight Data Recorder” that is mainly used for accident investigations (widely known as “Black Box”), there are also recorders for regular operations. These recorders are often called “Quick Access Recorders” (QAR). QAR data is analysed in terms of safety, efficiency and other aspects in Flight Data Monitoring activities for airlines and is furthermore an integral part of the research project SafeClouds.eu.
image2017-7-14 17_54_24

Figure 1: Example for a QAR (Source: https://www.safran-electronics-defense.com/aerospace/commercial-aircraft/information-system/aircraft-condition-monitoring-system-acms)

Aircraft are very complex systems with a large number of sensors constantly recording measurements. Important parameters regarding the aircraft state, including position, altitude, speed, engine characteristics and many others are recorded by the QAR. Depending on the aircraft type and airline, the number of recorded parameters can reach several thousand.

As a digital device, the recording uses binary format. In other words, if we look at the QAR data we would only see a bit stream, i.e. a sequence of 0 and 1. In order to use the data and investigate, for example the aircraft position, two additional components are necessary. First, logic is needed to determine how the data is written into the bit stream. This is given by an ARINC standard and two versions are presently used: ARINC 717 standard is used for older aircraft types and the ARINC 767 is used for newer aircraft types. Second, a detailed description of the location of any considered parameter in the bit stream is needed. This is given by a “dataframe” which is a text document of up to several hundreds of pages.

image2017-7-14 17_54_34

Figure 2: Overview (Source: “Flight Data Decoding used for Generating En-Route Information based on Binary Quick Access Recorder Data”, Master thesis, Nils Mohr, Technical University of Munich)

File Formats

One of the advantages of data stored in binary format is storage efficiency. The size of the same flight data file stored in binary format compared to being stored in engineering values (e.g. in a CSV file) might be ten times smaller. Considering the research project SafeClouds.eu or the shared framework for flight data such as ASIAS of the FAA, FDX of IATA or Data4Safety of EASA which collects millions of flight data, an efficient storage is obviously needed.

However, storing flight data in binary format then requires an efficient way to transfer the binary data into engineering values. Considering the bit stream logic, two parts are necessary. First, the bit stream logic (provided by the ARINC standard) needs to be represented in a decoding algorithm. Second, the dataframe information, i.e. which parameter can be found in which part of the bit stream needs to be accessible to the decoding algorithm.


Recorded parameters have different characteristics. For example, they can be numeric, alphanumeric or characters. Depending on these characteristics, different decoding rules have to be applied. As an example, a temperature recording of 36.5 °C with a linear conversion rule is considered in the following figure.

image2017-7-14 17_54_46

Figure 3: Simple Decoding Example (Source: “Flight Data Decoding used for Generating En-Route Information based on Binary Quick Access Recorder Data”, Master thesis, Nils Mohr, Technical University of Munich)

Starting from the bit stream, just specific binary values are relevant for the temperature recording. As mentioned above, this information can be found in the dataframe. The combination of all bits leads to a number in the binary system, which can then be transferred into the associated decimal value. Applying the conversion rule for linear parameters gives the result 36.5. Information about these rules as well as the unit, in this case degree Celsius, can be found in the dataframe.


The data that is recorded by civilian aircraft in their daily operation contains valuable information that can be used for airline safety analyses. Due to the nature of the recording, the data is generated in binary format. To make the data accessible and readable for the analysts, a decoding algorithm is applied. For the development of this algorithm, information about the recording logic and for all the considered parameters must be available.

Author: Lukas Höhndorf (TU Munich)

VISTA: priorities and building a credible model

Setting priorities and building a credible model

In Vista, capturing the level of development of the ATM system in the 2035 and 2050 horizons is critical, and we need to ensure that the most relevant scenarios for stakeholders are prioritised during the project. A consultation with relevant expert stakeholders has been conducted to help us with these tasks. The consultation focused on obtaining the experts’ view on key aspects of the project, namely: identification of potential missing metrics for the different stakeholders; prioritisation of the metrics generated by the model; identification of potentially missing factors and possible values considered for them; ranking of foreground factors (see previous blog) by relevance; ensuring that none of the factors identified as background factors should instead be considered as foreground; prioritisation of background scenarios and identification of the level of maturity of the system for 2035 and 2050 and, finally, understanding which particular results produced by Vista would be of particular interest to experts and stakeholders. The consultation questionnaire comprised twelve detailed questions and was targeted at high-profile experts in the ATM field.

The result of this activity allowed us to prioritise the metrics and scenarios that will be modelled and ensured that we had not missed any relevant source for regulations or technical evolution of the system. A second consultation is planned in order to review the firsts results obtained with the model. With these consultations, Vista maximises its impact on the community, addressing the topics that are relevant to stakeholders and validating the results obtained.

Another strength of Vista is the inclusion of key stakeholders, not just as consultation body, but as core partners in the project. Vista benefits from such partnership with airlines (SWISS, Norwegian and Icelandair), a FABEC ANSP (Belgocontrol) and airport experts (EUROCONTROL). Dedicated site visits have been carried out in Reykjavik, Oslo and Zurich to further understand the airlines’ business models, needs and projected system evolution. These visits also allowed the modelling team of Vista to have first-hand access to the strategic, pre-tactical and tactical management of airlines’ operations. This access ensures that the model captures the impact of the different factors as closely as possible to reality. Moreover, the airlines’ involvement in the project provides crucial data and validation of preliminary results. Similarly, planned meetings in Brussels and London with Belgocontrol and EUROCONTROL will ensure that the vision of ANSPs and airports are properly considered in the model.

ECTL_logo      belgocontrol_logo    Icelandair_NO


 640px-Swiss_International_Air_Lines_Logo_2011.svg   norwegian-logo

Moving the people to the terminal? Why not move the terminal to the people?

The question of ground access to airports is the object of many studies. How do we get people to the airport quickly, efficiently and sustainably? A previous blog post touched on the many different means people use to accomplish this part of their journey.

One of the major options that is often pursued is the creation of a train line joining the airport to its host city. However, while this city is often the most frequent origin/destination of travellers using the airport, it by no means accounts for the majority of surface access/egress journeys.

For example, fewer than 54% of access/egress journeys to/from London Heathrow (LHR) come from the whole of Greater London, much less from the central part London that is served by the Underground and the Heathrow Express train. In fact, the Express trains between them only account for 13% of terminating passengers which, while certainly not negligible, leaves seven out of every eight passengers to take a different mode of transport. 61% of passengers to LHR use private transport. After all: who want’s to join all of the congestion travelling into the centre of a big city from the suburbs (or beyond) where they live, just to get the train out to the airport?

So what’s the solution? Heathrow Airport Ltd (HAL) is pursuing a plan as part of its “Heathrow 2.0” initiative to ensure that the 100 largest cities in the UK are linked to LHR by train with no more than one connection. More rail access will be available when the “Crossrail” line that will run between Brentwood and Reading through London has been completed.

We can also make it easier to park, reducing time to do so and the walking time needed to catch the shuttle to the airport. Stanley Robotics, a French startup, is proposing a robotic valet that will pick your car up at the entrance to the car park and park it for you, fetching it for you when you return.

Enter the toast-rack.

Airports like LHR are moving to the “toast-rack” layout. With the creation of Terminal 5 (T5), satellite terminals (5B and 5C) are placed between, and perpendicular to the runways, fed from the main terminal (5A) at the end. An air-side underground train takes passengers from the check-in and security in 5A to the satellites.

 Annotated LHR

The new “Queen’s Terminal” will eventually have the same design.

But when T5 was built both the Underground Piccadilly line and the Heathrow Express were extended – parallel to the air-side underground train serving the satellites – to bring passengers land-side to 5A. Move them west to move them back east – not very efficient!

Why not move the terminal, instead of the people?

Isn’t it time we started re-thinking how we design our airports? Is there any reason why the terminal needs to be where the runways are? Previously, it has been possible to check your bags in at a railway terminal before boarding your train/bus to the airport (at London Victoria for Gatwick, for example) but this is not really moving the terminal to the people.


With Crossrail, a new underground branch line is being built from the London-Reading line (access from London only) to LHR, bringing more land-side passengers (but only some of them – many will still come by car) – but inconveniently not serving T5. Now if Terminal 5 check-in, baggage claim, security, etc. had been constructed on the London-Reading line, the same investment could have paid for an air-side line that would link in with the T5 air-side line and carry every passenger to 5A, 5B, 5C and beyond.

Imagine a terminal only a few kilometres from the runways, where the train line and the motorway access already exists. For LHR, this could have been at Iver, in an area served directly by the existing train line (and the same two motorways as LHR is) but with enough room for all of the airport’s needs with space for a complete airport business, hotel and shopping city without anything being bounded by runways, taxiways, gates, service areas etc. The car parks could have been right next to the terminal instead of, as is the case with T5, being so far away that the airport has had to spend £30m to provide personal transport “Pods” to transfer people to and from the terminal.
Annotated Iver

This air-side line could even be extended to a second or third terminal, closer to other access points to the city. In the case of a multi-airport city like London, one could even envisage an air-side railway linking all of the air-sides (Gatwick, Heathrow, Luton and Stansted), and their displaced terminals, enabling passengers to use the terminal nearest to them and to fly from the runway of their airline’s choice.

Complete separation

Having only air-side activities where the runways are and leaving the land-side activities where the people are is a much cleaner solution that reduces airport access time, and provides more space for land-side activities. And once the concept of separating the land-side from the air-side is accepted, the air-side/runways can be located somewhere where fewer people will be annoyed by the noise. If staff and passengers have to use a land-side terminal access miles from the air-side, the pressure to live near the airport for easy access would move away from the runways, causing less encroachment into noise-impacted areas.

For Heathrow, it’s too late to think of implementing such a system now; the investment in Heathrow Express, the Crossrail link, T5, the Queen’s Terminal, the Pods, etc. has already been made.

But when the next new airport is built, perhaps it would be worthwhile to think that, instead of annoying both travellers and residents by building terminals and runways together, it would be much better to put the terminals close to the people and the runways far away from them.

Author: Pete Hullah (EUROCONTROL) as part of DATASET2050 project

European door-to-door mobility workshop! 20th Sept, Madrid

Save the date: European door-to-door mobility workshop, next 20th September 2017, 10:30-16:00

Are you interested and/or doing research in the field of passenger transportation and European mobility? Are you interested and willing to improve current door-to-door passenger experience and metrics? Are we close to the 4 hour door-to-door European objective?  Come and join the free second www.DATASET2050.com workshop!

The event, hosted at Google Madrid Campus will mix active debate and participation from all the workshop attendees with presentations from top entities in the field: both member of DATASET2050 consortium and key invited external speakers!

-Event registration is free but with limited places available. Register below. 

-Final agenda  to be attached to this page in the following days. Already confirmed presentations/speakers comprise:

  • Passenger and demand profiling
  • (Door to door) mobility models and metrics
  • Novel future (transport) concepts
  • ACARE WG1 - SRIA update / Long term EU mobility goals
  • Metropolis Project (TU Delft)
  • Sustainable airports, airport cities, aerotropolis
  • many more!

-Further info and logistics are available here: Download our complete guide

See you next 20th Sept in Madrid!


Note: This DATASET2050 Workshop is taking place in tandem with the ACARE WG1 meeting (19th September Madrid -restricted to ACARE members).


Are regulatory and business changes aligned with key ATM objectives? (Introducing the Vista project).

How will different regulatory and business changes affect the KPIs of ATM stakeholders in the 2035 and 2050 horizon? Are the various foreseen changes aligned to obtain improvements in key indicators? Will trade-offs emerge from different policies to be implemented? What is the impact of technology changes on different economic developments?

Vista considers these questions and examines the effects of conflicting market forces on European performance in ATM, through the evaluation of impact metrics on four key stakeholders (airlines, passenger, airports and ANSPs), and the environment. The project comprises a systematic, impact trade-off analysis using classical and complexity metrics, encompassing both fully monetised and quasi-cost impact measures. Vista will model the current, 2035 and 2050 timeframes based on various factors and their potential evolution.

The factors modelled in Vista influence the stakeholders’ choices: prices of commodities and services, regulations from national and supranational entities, and new technologies are all part of a complex socio-economic system that results in evolving business models, passenger choices, etc. These factors are divided between regulatory and business factors. Business factors may affect technology uptake and economic changes. Regulations, on their turn, may act as enablers of the technological and operational changes, e.g., the Single European Sky regulatory framework, or may directly affect the performance of some stakeholders, such as air passenger rights.

The different factors considered have been obtained from a literature review of regulations, projects, technological and operational changes. Concerning the regulations, the different areas of the ATM network and regulations applying to them have been reviewed. Communications and strategies laid down by, or foreseen by, regulatory trends have been used to identify the possible evolution of these regulations. The main source for the business factors are the SESAR projects, in particular, the high-level goals of SESAR described in its Master Plan (Ed. 2015), as well as more precise information related to the SESAR workpackages. The expected impacts of operational sub-packages in SESAR will be used to identify the impact of these on the evolution of KPIs. Some more long-term R&D research activities are also considered, in particular to be used in the 2050 scenarios of Vista. Other business factors include the price of fuel, the business models of the airlines, and changes in demand linked to the socio-economic development of Europe. Regarding the latter, many factors will be considered as closely linked and the diverse possibilities of development will be significantly influenced by outputs such as the STATFOR forecasts.


In the Vista model, regulatory and business factors are classified between foreground and background factors. Background factors are grouped to generate background scenarios onto which the foreground factors will be tested. These background scenarios, identified below, define different possible evolutions for the 2035 and 2050 horizons and have been defined to identify the impact of the technology on different economic development scenarios.

Period Name Technology development Economic development
Current Current Current Current
2035 L35: Low economic, Low Techno Trajectory-based performance as defined in SESAR Low economic development
M35: High economic, Low Techno Medium economic development
H35: High economic, High Techno Performance-based performance as defined in SESAR
2050 L50: Low economic, Low Techno
M50: High economic, Low Techno High economic development with an increment on environmental-friendly passengers
H50: High economic, High Techno Enhanced performance-based performances as defined in SESAR

Examples of foreground factors, the impact of which will be individually assessed, include: regulatory changes on passenger provision schemes, fuel charges, or the introduction of smart ticketing. Foreground factors can also be grouped in higher-level categories to identify the impact of different policies on the scenarios: environmental mitigation policies (e.g., emission scheme and noise pollution regulation), regional infrastructure usage (e.g., airport access, regional infrastructure development), passenger focus modifications (e.g., passenger provision schemes and reacommodation tools) and Single European Sky (e.g., 4D trajectory management, traffic synchronisation, airspace charges). The qualitative impact of the factors, both foreground and background, on each part of the model has been identified.


Vista will necessarily model all ATM phases: strategic, pre-tactical and tactical. Factors will have different impacts on these time scales. The Vista model has been created following these temporal layers. A scenario, defined as an instantiation of foreground and background factors, will be executed by the model. The strategic layer, will use an economic model to balance the strategic demand and capacity of the different elements in the ATM network and schedules will be provided to the pre-tactical layer. The pre-tactical layer will generate flight plans, passenger itineraries and ATFM regulations. These flights and passenger itineraries will be executed tactically using the Mercury model . Mercury model has been developed on previous projects (POEM , ComplexityCosts) and allow the simulation of flights and passengers itineraries obtaining not only traditional flight-centric metric but also passengers focus ones. See our next blog (August) for more information regarding Vista tactical layer. Being a stochastic model the output of the different layers will be consolidated to analyse the results and understand the horizontal and vertical trade-offs identified. Finally, a learning loop will be used to give feedback to the strategic layer on the metrics obtained and, based on the initial expectations of the model, to adjust strategic behaviour. This will ensure that, after several iterations, a stable and realistic realisation of the scenario is obtained.

In order to capture the impact of the different factors on the model and the evolution of the system, dedicated site visits and consultation with experts have been performed (see next blog entry for more details). The Vista approach and methodology was been presented at the 2017 World ATM Congress (7-9 March 2017, Madrid) and at the 2017 ART Workshop (26 April 2017, London).

Towards user-centric transport in Europe – Challenges, solutions and collaborations

The EU projects Mobility4EU (http://www.mobility4eu.eu/) and MIND-SETS (http://www.mind-sets.eu/) jointly organized the event “Towards user-centric transport in Europe – Challenges, solutions and collaborations” in Brussels in May. The aim was to bring together stakeholders from different areas to discuss innovations in transport and mobility addressing future challenges for the European transport system (http://www.mobility4eu.eu/midtermevent/). One part of this event were several interactive sessions in which the participants discussed various issues relating to the improvement of current transport practices. The partners of DATASET2050 acted as facilitator of the session “Enhancing multi-modal collaboration between service providers”, in close collaboration with the EU project PASSME.

Applying the “World Café” approach, this session focused on the better integration of different service providers in order to facilitate a seamless journey for the passenger (see the figure below for examples of existing and future intermodal concepts, these will be addressed in more detail in upcoming deliverables of DATASET2050). Within different groups, simulating a round table in a relaxed atmosphere, participants of the workshop discussed a variety of approaches that reduce friction along the journey. One aspect which had been discussed extensively is the establishment of a legal framework accompanying the closer collaboration of service providers. Legal issues concern the liabilities in terms of delays, lost luggage or reimbursements. Furthermore, data sharing both between providers as well as between providers and passengers had been highlighted as being a main contributor to a seamless journey. Passengers receiving real-time information as well as alternative travel options along the journey have to be enabled by a shared data pool all providers have access to. This, however, requires a clearly defined set of rules and responsibilities regarding data handling and passenger privacy issues in order for all parties to participate. In terms of passengers’ data privacy concerns, studies have shown that passengers agree to share their personal data with service providers if both data security can be guaranteed and their journey and travel experience is improved.

In terms of collaboration, the “last mile”, which covers the distance between the final destination and the last stop of e.g. public transport, often constitutes a bottleneck within the seamless journey. Therefore, ideas within the workshop circled around passengers pooling their demand and sharing a taxi in order to get to the airport or the train station. Or autonomous cars providing an option to cover the last segment of the passenger journey by efficiently assigning resources to the time and location they are needed. Overall, participants argued that there is no single solution which fits all passenger needs but that customization and differentiation across distinct groups have to take place.


inter-modal conecepts


9292 / https://9292.nl/
Airbus / http://www.airbus.com/de/
Airportbus Munich / https://www.airportbus-muenchen.de/
Air-Rail / http://www.air-rail.org/index.php?lang=EN
Air-Train / https://www.globalairrail.com/awards/24-awards/awards-2016/216-airtrain-city-marketing
Ally / https://www.ally.com/
Allygator / https://www.allygatorshuttle.com/
Amtrak / https://www.amtrak.com/home
Bike Train Bike / http://www.bitibi.eu/
Blacklane / https://www.blacklane.com/de
Boring Company / https://www.boringcompany.com/
Bus and Fly / http://busandfly.com/de/page.php
Cabify / https://cabify.com/
Cambio / https://www.cambio-carsharing.de/
Car2Go / https://www.car2go.com/DE/de/
Chu Kong Shipping Enterprises / http://www.hulutrip.com/product/41617.html
Citybike / https://www.citybikewien.at/de/
Citymapper / https://citymapper.com/rhineruhr
Clipper / http://clippercard.com
Cotai Waterjet / http://www.cotaiwaterjet.com/airport-ferry-services.html
Deutsche Bahn / https://www.bahn.de/p/view/service/fahrrad/call_a_bike.shtml
DriveNow / https://www.drive-now.com/de
Drivy / https://www.drivy.de/
Ehang / http://www.ehang.com/
Emmy / https://emmy-sharing.de/
Ferrara Bus & Fly / http://www.ferrarabusandfly.it/
Flinkster / https://www.flinkster.de/
Flightcar / http://farewell.flightcar.com/
Fraport / http://www.fraport.de/de.html
Free2Move / https://de.free2move.com/about
Gett / https://gett.com/
GoEuro / https://www.goeuro.com/trains/
Hannovermobil / https://www.uestra.de/mobilitaetsshop/hannovermobil/
Hyperloop One / https://hyperloop-one.com/
Iberia / http://www.iberia.com/de
Kobe – Kansai Bay Shuttle / https://www.kobe-access.jp/eng/
Lyft / https://www.lyft.com/
Memobility / http://www.memobility.de/
MobilityMixx / https://mobilitymixx.nl/home.html
Moovel / https://www.moovel.com/de/de
Mozio / https://www.mozio.com/de-de/
Mycicero / http://www.mycicero.it/
Mydriver / https://www.mydriver.com/de/
Network Rail / https://www.networkrail.co.uk/
Octopuscard / http://www.octopus.com.hk/home/en/index.html
ÖBB / https://www.oebb.at/de/
Oystercard / https://oyster.tfl.gov.uk/oyster/entry.do
Rallybus / http://rallybus.net/
Rome2Rio / https://www.rome2rio.com/de
SBB / https://www.sbb.ch/de/home.html
Stadtmobil / https://www.stadtmobil.de/
Swiss Helicopter / http://www.swisshelicopter.ch/DE/
Tamyca / https://www.tamyca.de/
Taiwan High Speed Rail / https://www.thsrc.com.tw/index_en.html
Thalys / https://www.thalys.com/de/de/
Touch & Travel / http://www.7mobile.de/handy-news/touch-travel-bahnticketkauf-mit-dem-smartphone-moeglich.htm
Turo / https://turo.com/
Tuup / http://tuup.fi/
Uber / https://www.uber.com/
Union Station Denver / http://unionstationindenver.com/
Urbanpulse / http://www.urbanpulse.fr/
Velib / http://www.velib.paris/
Voom / https://www.voom.flights/
VW (Sedric) / http://www.discover-sedric.com/de/
Wideroe / http://www.wideroe.no/en
Wmata / https://www.wmata.com/
Yugo / https://getyugo.com/barcelona
Zee Aero / http://www.zee.aero/

Augmented reality and data visualization (in aviation)

Present-day technology is so powerful that the perception of reality can be easily and realistically modified with IT tools, providing users withan experience beyond “simple” reality. This is achievable by mixing real-world environment elements supplemented and/or augmented by computer-generated inputs. The current post unpacks this topic, focusing specifically on the data visualization aspects. In brief, augmented reality can take two approaches:

  • First, inventing totally new scenarios, in which the user becomes part of a “parallel universe”. Supplementing the real-world environment with an unreal one; either a virtual place (video game) or a different location (i.e. another real location). This is the case of futuristic 90’s and early 2000’s alike head-mounted displays with users’ eyes looking at full screens recreating other places. The ergonomics aspects are usually modest for most of the applications due to the head-mounted displays weight and size.


  • The second, and closer to “data visualization” area is the so called “mediated reality”. The real-world environment enhanced by virtual elements displayed in glasses, windscreens etc. In them, additional information/data is provided. The real challenges is to decide what, how and when to display the information, without requiring users to look away from their usual viewpoints, while providing extra value. The integration and user experience is much more natural and enjoyable than the fully immersive systems.
Research project Augmented Reality - contact-analogue Head-Up Display (10/2011)

Research project Augmented Reality – contact-analogue Head-Up Display (10/2011)

In this context, one of the very early examples of head-up displays can be found precisely in aviation, almost 80 years ago. In 1937, the German ReviC12/A fighter aircraft included a basic reflector sight indicating some basic aircraft magnitudes such as speed and turn rate, to reduce the (visual) workload of pilots in case of extreme maneuvering
Nowadays virtually all modern fighters (F18, F16, Eurofighter) use head-up displays. The most modern versions (F35) do not have head-up displays, and instead include helmet mounted displays, ensuring the proper orientation of the user’s head, for all circumstances.
One of the trending topics of augmented reality within aviation is its usage in air traffic control (ATC), particularly in Tower environments. Below are two common approaches:

  • Visual information is enhanced to ease identification and tracking of aircraft. This includes tools similar to head-up displays and/or helmets-displays that enhance the information (providing for instance, aircraft ID, scheduled times, etc). This approach could be extremely useful in low visibility conditions by facilitating the tower ATCOs tasks. It also avoids dividing attention between the primary visual field (the window) and the auxiliary tools (surface radar, strips etc).

Screen Shot 2017-02-23 at 15.05.29maxresdefault

  • The extreme version is a complete virtual control tower, the so called “remote tower”. ATC would have remote control rooms with video-sensors on-site, including augmented reality enhancements. The synthetic augmentation of vision increases the situational awareness at the airport, especially during poor visibility conditions, or blocked line-of-sight areas due to airport geometry. It additionally provides benefits in terms of cost saving (no need to build and maintain control tower facilities) and a more efficient use of human resources (potentially serving multiple airports with low traffic events from a centralised location). Research in this field started in FP6 project “ART” and is now being progressed by SESAR WP6. In fact, Örnsköldsvik/Gideå airport is the first on the world deployment of remote tower, in late 2015, by the Swedish LFV. In US, Fort Collins-Loveland Municipal Airport was the first approved and tested airport with a remote tower in 2016.

Screen Shot 2017-02-23 at 15.08.47
For the air passenger and mobility context, augmented reality and the wide range of solutions providing additional real-time information to passengers is taking off as well. (No pun intended.)
These technological innovations include indoor location tracking, real-time information on boarding gates, real-time updates on flight delays, and information on airport facilities and shops. This is also being expanded to knowing the number and location of available parking spaces to facilitate the passenger experience in the (sometimes not so easy) airport processes. For example, Copenhagen airport, in collaboration with SITA, created the very first augmented reality indoor app in 2012. Now there is an endless list of both airlines and airports with similar apps.
Do you think augmented reality together with innovative data visualization can have a significant impact in future aviation?
What are its challenges and potential benefits?
We’re interested in hearing your thoughts and ideas.

On maps

How are “mobility” and trips visualized and represented? Well, the most direct, intuitive way of doing so, is using maps. Representations, converting the 3-dimensional earth (*sphere*) to a flat  2-dimensional surface. This post is about maps, map properties, map distortion and curious maps. We hope you enjoy it!

Mapping the earth, or parts of it, is a classic, well-studied problem. For hundreds / thousands of years, cartographers and mathematicians have come up with different methods to map the curved surface of the earth to a flat plane. The main problem is that you cannot do this perfectly, (Theorema Egregium). The shape, area, distances and directions of the surface cannot be represented properly at the same time on a map.


Shape: If a map preserves shape, then feature outlines (like country boundaries or the coast lines) look the same on the map as they do on the earth. A map that preserves shape is conformal. The amount of distortion, however, is regular along some lines in the map. For example, features lying on the 20th parallel are equally distorted, features on the 40th parallel are equally distorted (but differently from those on the 20th parallel), and so on. The Mercator projection is one of the most famous and well-used shape-preserving maps:


Area: If a map preserves area, then the size of a feature on a map is the same relative to its size on the earth. For example, on an equal-area world map, Spain takes up the same percentage of map space that the actual Spain takes up on the earth. In an equal-area map, the shapes of most features are distorted. No map can preserve both shape and area for the whole world, although some come close over sizeable regions. Sinusoidal projection is an area-preserving projection:


Distance: If a line from a to b on a map is the same distance (accounting for scale) that it is on the earth, then the map line has true scale. No map has true scale everywhere, but most maps have at least one or two lines of true scale. For instance, in the Casini projection, the distances perpendicular to central meridian are preserved:


Direction: Direction, or azimuth, is measured in degrees of angle from north. On the earth, this means that the direction from a to b is the angle between the meridian on which a lies and the great circle arc connecting a to b. If the azimuth value from a to b is the same on a map as on the earth, then the map preserves direction from a to b. No map has true direction everywhere.

Finding the compromise: Most of the maps used are compromise solutions, partially preserving some of the above mentioned properties. The most used one (by far) is the one you can find in Google Maps, OpenStreetMaps etc. called Web Mercator, Google Web Mercator, WGS 84 Web Mercator or WGS 84/Pseudo-Mercator. It is a variation of the Mercator projection, ignoring the ellipticity of Earth for faster computation:


The Winkel tripel projection. “Triple” stands for trying to minimize errors in three properties at the same time: area, direction, and distance. The Winkel tripel is the arithmetic mean of different projections (equi-rectangular, area and shape preserving)


There is even a whole family called Myriahedral projections. These consider the earth *sphere* to be a polyhedron with a very large number of faces, a “myriahedron”. This myriahedron is cut open into small pieces and unfolded. The resulting maps have a large number of subareas that are (almost) conformal and that (almost) conserve areas. The location of the map interruptions can be “selected” (oftenly using sea areas etc)

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Some ingenious representations mix the approach from Myriahedral projections and other property-preserving projections. e.g. the Goode Homolosineprojection:


All the previous projections provoke distorsion. There is no perfect projection. In the nineteenth century, Nicolas Auguste Tissot developed a simple method for analysing map-projection distortion. An infinitely small circle on the earth’s surface will be projected as an infinitely small ellipse on any given map projection. The resulting ellipse of distortion, or “indicatrix”, shows the amount and type of distortion at the location of the ellipse. Some examples for the most-used projections are given below.


If all the previous was not enough, it just leaves the door open to other projections that represent additional variables in maps, such as socio-demographic or technical indicators.

A map with country size proportional to population:


Proportional to number of immigrants:


Proportional to the number of tourists (Spain the biggest country in the world!):


Or even proportional to the total number of flights (this is one of my favourites!):


Some references and further reading on the topic:

How do you catch a plane?

How do you catch a plane? More interestingly: what are the stages of your door-to-door journey when an airline flight is involved? They’re most likely not all the same as anyone else’s.

There are a myriad ways of getting from your starting point (home, office, hotel) to the airport – from “door” to “kerb”. It could be by private car – whether “kiss-and-fly” (driven by family or friend), a ride-share with another passenger/co-worker, a taxi/minicab or their modern app-based equivalents, or we can just drive ourselves and park in the long-term or short-term car park (or maybe an off-site car park which then took you to your terminal by shuttle bus). It could be by bicycle or motorbike. It could be by bus, coach, tram, train, metro, or a combination of these – but how did you get to the stop/station for first one; walking, taxi, driving, “kiss-and-ride”, cycling – and where did the last one drop you off: the terminal, the airport transport hub? You may have driven, and then had to return, a hire car (if this is a return leg or your trip) and then took the hire company’s shuttle. If you left from an airport hotel, you most probably took their shuttle.


Getting through the airport (from “kerb” to “gate”) also involves many options. Did you check in online or do you have to do it at the terminal? Do you have bags to check in? Do you have to go through passport control? How long is the queue at the security check? How much buffer time did you leave, that you can now spend browsing around the shops? How many miles do you have to walk to get to your gate? Is your flight delayed?

Your answers to these questions (and their equivalents for the “gate” to “kerb” and “kerb” to “door” legs once your flight has landed), as well as the process for the actual flight(s) from gate-to-gate (including any transfers), have a bearing on how long your total journey will take. To be able to determine where there is room for reduction in this journey-time, and where research must be directed to initiate this reduction, in order to meet the ACARE goal of 4 hours door-to-door for intra-EU journeys, the DATASET 2050 team have analysed the component times of the current air journey in detail. This work is presented in the project’s deliverable 4.1 – Current Supply Profile.

Data for such analysis is hard to come by. Much of it is proprietary and, if it’s available at all, is sold at a high price – too high for this project. That which is available generally concerns all passengers, rather than just those on intra-EU travel; are people really likely to ride on one of the scheduled overnight coaches from Edinburgh to Heathrow to take a short-haul flight?

Making use of tools such as those provided by Google Maps, DATASET2050 researchers have been able to see the time taken to access airports by car, bicycle and public transport for a selection of airports.

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 Berlin Tegel access-egress times by (L-R) bicycle, public transport, and car

(NB: scales are different, see them full size below)

These results and the many others included in D4.1 will help colleagues working on the next steps in the DATASET2050 project determine which parts of the different segments of your door-to-door journey can be speeded up, and where research and development is needed to further reduce our journey times.






Airport Economic Value study published!

The Modelling Airport Economic Value Study recently published (link here) has been made by the University of Westminster (Andrew Cook, Gerald Gurtner, Graham Tanner and Anne Graham) and Innaxis Research Institute (Samuel Cristobal), supporting EUROCONTROL (Denis Huet and Bruno Desart) within SESAR Project 06.03.01. The study provides a better understanding of the interdependencies of various key performance indicators (KPIs) and assesses the existence and behaviour of an airport economic optimum, in a similar way to the early 2000s, when estimating the economic en-route capacity optimum.


By gathering for the first time real operational, financial and passenger-satisfaction-related data over 32 European airports, it was possible to develop and calibrate a model which produces reliable and realistic results. The fully calibrated results show the presence of a trade-off between the cost of extra capacity and the increase in the number of flights operated. As a consequence, all 32 airports exhibit a maximum in net income as a function of capacity, when the marginal cost of operating extra capacity is sufficiently low. This threshold in the marginal cost is, however, rather different across airports, and only a few airports can sustain a high cost of capacity: these are the largest and most congested airports, which clearly need extra capacity. This threshold is roughly consistent with the airports’ current operational cost of capacity, which means that they should be able to manage this growth, subject to the availability of investment.

The team has also developed a tool that provides access to all the features of the mathematical model with out having to dig into the equations. The underlying mathematical module is written in Python, while the interface is written in Matlab. The communication between the modules is transparent to the user and the software is capable of auto-calibrate the airport model using the existing or new data. The tool is flexible to explore the parameter space and different views of the output variables can be selected for a better understanding of the model outcomes. Results can be saved then in common format for further use (txt, csv, png, fig, etc.)

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We warmly invite you to read the full report here!

Congrats to Samuel/UoW colleagues for such a superb study 😉


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