European mobility for the future: strategic roadmaps and performance assessment

What are Europe's mobility goals and how can progress towards these goals be measured? What would make up a feasible set of key performance indicators (KPIs) for mobility? And which major aspects of the work towards creating Europe's future transport system are addressed in the Mobility4EU Action Plan?

These are some of the key questions that will be discussed at a workshop organised by the EU-sponsored CAMERA and Mobility4EU projects on 15th June in Brussels.

The aims of the “European mobility for the future: strategic roadmaps and performance assessment” workshop are to acquire feedback from experts from different mobility sectors on the development of a strategic roadmap for the European transport system (Mobility4EU Action Plan) and to discuss the research requirements, gaps, and bottlenecks shown up by this roadmap (Progress towards EU mobility goals).

The workshop will consist of two distinct sessions: the morning session on the Mobility4EU “Action Plan”and the afternoon one on the CAMERA “Progress towards EU mobility goals” topic. Both of these sessions will rotate through three parallel round-table discussions, and participants will actively contribute to the development of the Action Plan and to the identification of important aspects to be taken into consideration when designing Europe's future transport system.

Do you think you could bring something to these discussions? Are you interested in hearing what other experts think? Don’t miss this opportunity: take a look at the agenda and register for the workshop now! Admittance is free but places are limited.

EUROPEAN MOBILITY FOR THE FUTURE
STRATEGIC ROADMAPS AND PERFORMANCE ASSESSMENT

BRUSSELS, 15 JUNE 2018 Blue Point Brussels
Bvd. Auguste Reyers 80
1030 Brussels

www.h2020camera.eu
micol.biscotto@dblue.it
annika.paul@bauhaus-luftfahrt.net

www.mobility4EU.eu
marcia.urban@bauhaus-luftfahrt.net
beate.mueller@vdivde-it.de

Mobility metrics and indicators rethought

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Performance is about comparing some output of a system with some level of expectations. The issue of setting the right level of expectations is certainly a major issue by itself, but choosing the right metrics to measure is probably even more difficult.

This difficulty comes from the fact that Key Performance Areas (KPAs) live in a different world than Key Performance Indicators (KPIs). KPAs live in a qualitative world, where general ideas are thought to be important for human beings. For instance, ‘safety’. KPIs on the other hand belong to a quantitative world of ‘cold values’ — floats, integers — observed on the real world. Matching these two worlds is like getting into Mordor: first you think that it will be obvious, then you think that it will be impossible, and you finally pick a way because it is pretty much the only one available.

Indeed, the potential KPIs that one could imagine are fortunately severely restrained by reality and what we can observe in the system. For instance, in DATASET2050 we were trying to define an indicator for the ‘seamlessness’ of a trip, something which is important for all travelers without a doubt. Important, ok, but what is it exactly?

Seamlessness is about the perception of travellers. As a consequence, it is highly subjective, which by definition cannot be part of an indicator, because an indicator is meant to be objective. So instead of a top-down approach where we use the question ‘What would be the best metrics to measure in order to represent seamlessness?’, we are left with a bottom-up approach consisting in ‘Among the ones I can measure, what are the metrics which would be related somehow to seamlessness?’.

So, what can we measure? For many years now, sociologists and psychologists use the ‘cognitive load’ to have a measure of the effort needed by a brain to accomplish a given task. Seamlessness is about being able to forget the trip itself and not actively be forced to take decisions or looking for information for the continuation of the journey. We thus defined a first indicator, which is the total cognitive load of a given trip for the passenger as a measure of seamlessness. Ok, but how do you measure cognitive load in reality?

Well, you don’t, as least not on a large scale. And here comes the second step of the search for a good indicator: can we find something easily measurable which is an approximation for what would be a perfect indicator?

In the case of seamlessness, we have to go back to how the travel unfolds. For instance, what is the difference between:

1) depart from home, take a taxi, take a train, take a taxi, arrive at destination.vs:

2) depart from home, take a taxi, take a train, take another train, take a taxi, arrive at destination.

Easy: there is one train more. Ok, but what makes you choose the first option over the second if both have the same travel time, price, etc.? Well, the first is easier, right? You do not have to think about getting off the train, find the next one, wait, get in train, possibly struggling to find a spot to seat, etc. So the idea that the first one is easier than the second one comes ultimately from the ‘continuation’ property of the actions you are taking, which is associated with a low cognitive load dedicated to the journey. In other words, taking different actions during a trip is more annoying that taking only one action.

Following this idea, DATASET2050 defined the journey as a series of ‘phases’ and ‘transitions’. ‘Phases’ are typically long with a low cognitive load dedicated to the journey, whereas ‘transitions’ are short and require the active participation of the passenger in order to continue the journey. A simple indicator can then be defined as the number of transitions taken in a single journey, which is trivial to compute for nearly any journey, with very little data input.

A slightly more advanced indicator is to consider the time spent within the transitions — for instance, queuing times — compared to the total travel time. For instance, a small 45 minutes trip where one has to take three buses is quite tiring compared to a single-bus journey. This indicator requires more data, as the specific times in each of the segments are required. However, it is largely feasible to compute it with modern methods of data collection (e.g. GPS tracking). Giving a good balance between the measuralibity and its concetpual proximity with the initial KPA, this indicator is the one which has been selected as key performance indicator for seamlessness in DATASET2050.

In DATASET2050, we have gone through the exercise of finding the right indicator for all of the KPAs defined by ICAO, including safety, flexilibity, efficiency, etc. These concepts are sometimes too vast and need to be broken down into sub-KPAs, called “Mobility Focus Areas”. For all of them, several indicators have been defined, but we selected only one final KPI in the end per KPA. For instance, the KPA “flexibility” has been subdivided into “diversity of destinations”, “multimodality”, and “resilience”. Only on key indicator has been selected in the end, weighting the travel options by the distance between the potential destinations. All this work can be found in the public deliverable 5.1 of DATASET2050, soon available here

To conclude, the choice of a good indicator is thus dictated by the balance between the measurability of the metrics and its relationship with the overall concept. This is an important issue, as the indicators are then used by the policy makers to drive the system is a certain direction. And the quality of the indicator decides whether it is the right one or not.

Author: Gérald Gurtner (University of Westminster) as part of DATASET2050 post series

10 years later… and so much to come!

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This year marks Innaxis’ 10th Anniversary. A most remarkable date that we are very happy to celebrate and share with you. This decade -and the 30 projects developed so far- have provided us the opportunity of creating solid relationships with trusted partners and strengthening those links through successful collaborative stories. We consider you as part of this trusted network of partners, colleagues and friends and we feel very grateful for it.

As you surely know, Innaxis was founded with the objective of finding applications of Complexity Science to address problems of real socio-technical systems. From that (quite abstract) idea, we have done our (exciting and challenging) way to become a reference research organization at the confluence of Complexity Theory, Data Science and Societal Challenges, mainly in the Aviation and Mobility sector. This rapid evolution has been possible, and even more stimulating, thanks to people like you and organizations like yours, who have accompanied us in this journey.

Addressing real-life problems through breakthrough innovation requires a clear focus on applied research and a close collaboration with end-users to ensure the solutions meet users´ expectations and help in solving their needs. To effectively apply some of the research results obtained, we launched some time ago a new venture called Tadorea as a spin-off of Innaxis. Tadorea focuses on applying Knowledge Discovery and Machine Learning solutions to the aviation sector, leveraging on massive data analytics. We strongly believe on the potential of this promising area, and so David Pérez has been appointed as General Manager of Tadorea to take the lead of our spin-off efforts. David will nevertheless stay very well connected to Innaxis by being nominated to its Board of Trustees.

And it is also time to give new responsibilities to people who have been with us for a long time and have shown an outstanding capacity and performance, combined with personal styles which are quite unique. Both Paula López-Catalá as Programme Director and Samuel Cristóbal as Science & Technology Director, are newly appointed to these most relevant functions. Together with them, David, Arantxa Villar as Finance Director and Carlos Álvarez Pereira as President, will integrate the Management Team to pursue our -even more- ambitious goals in this new era which we are much willing to share, explore and enjoy with you.

Vista tactical model – Mercury: because passengers matter

Over the next decades, EU mobility is expected to progressively evolve from the gate-to-gate focus currently prevalent in the aviation and ATM industry towards a seamless and efficient door-to-door-orientated vision.  The paradigm shift from gate-to-gate (hence aircraft centered) to door-to-door (passenger-oriented) is present at virtually all strategic research documents and agendas. The paradigm shift is here to stay. From a passenger perspective, which of the following scenarios create more impact?:

  • Scenario A): a 8 minute delay in an aircraft arrival time with no connecting passengers
  • Scenario B): a 5 minute one that prevents a significant number of passengers doing a connection in that airport and subsequently expand their door-to-door trip in more than 10 hours

How can that impact be predicted in terms of time and cost? One of the very first research exercises was the POEM project (SESAR 1- WPE) etc. This project was the original seed of Mercury. Mercury has been afterwards improved, validated and completed in other reseach initiatives for SESAR and European Commission, reaching its current door-to-door status.

What is mercury?

Mercury is a modelling and simulator tool - a framework capable of measuring the performance of the air transport network. It provides a wide range of performance and mobility metrics, capable of describing in detail different air transport scenarios.

Mercury draws on extensive data, drawn from a wide range of industry sources, including airlines, airports and air navigation service providers. Mercury's data models have been demonstrated through over 5 years of research and development, plus industry consultation.

How passenger matter in mercury?

Mercury is the first air transportation network simulator that puts passengers in the centre. Each day of simulation the itineraries of more than 3 million passengers are reproduced. Each passenger has its individual profile, ticket and decisions to make. According to EU regulation 261/2004 passengers are compensated by delay and cancellations. Extended delays, aborted journeys, overnight stays there are all part of the Mercury simulator.

Of course airlines play a major role as well, Mercury incorporates costs models for canonical airline categories. Each of the airline decision of waiting for certain passengers, cancel a flight or even board the passengers and send a ready message even when a ATFCM slot was assigned is taken according to each airline rational cost model.

The secret ingedient: a spice of randomness

There is no way one could develop a simulator like Mercury taking into account every detail in the air transportation system. Some process are just too complex or simply put we do not understand yet. Whilst others are just exogenous factors far beyond the reach of the air transportation system. 

But what if we could use a different approach. In Mercury each day of operations is repeated, introducing small variations representing everyday uncertainty and exogenous factors.

Ultimately, small changes lead to completely different day of operations, delays and cancellations. Just similarly to what happens with some chaotic systems, the sensitivity to the initial conditions allow to explore overall trends and stable status, in some cases called emergence.

Interested in reading further info about Mercury? Click here to visit the website.

Author: Samuel Cristóbal (Innaxis)

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

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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.

Crossrail

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

European door-to-door mobility workshop, took place 20th September 2017, 10:30-16:00

The event, hosted at Madrid Campus (Google Space) mixed active debate and participation from all the workshop attendees with presentations from top entities in the field. See presentations below, some pictures will be available in the following days: agenda :

Videos here soon!

 

 

Note: The DATASET2050 workshop was organized planned in tandem with the  the ACARE WG1 meeting (restricted to ACARE members - 19th afternoon), and the CATER open event (19th morning), both  in ISDEFE premises (Madrid)

 

-Further logistics info (hotels, transport) available here: Download our complete guide.

 

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

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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

References

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/

On maps

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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.

1

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:

2

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:

3

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:

4

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:

5

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)

6

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)

7 8

 

 

 

 

 

 

 

 

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

9

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.

10

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:

11

Proportional to number of immigrants:

12

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

13

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

14

Some references and further reading on the topic:

DATASET2050 presentation at Data Science in Aviation Workshop (EASA, Cologne-Germany)

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The annual event exploring Data Science in Aviation (ComplexWorld funded; organized by Innaxis) has recently celebrated its fourth edition this past September 8th 2016. The event was hosted on the EASA premises in Cologne, Germany . This year it highlighted a presentation of the DATASET2050 project, “Data Science for Mobility”, by project coordinator Samuel Cristobal (Innaxis).

5-1

 

 

On the Data Science In Aviation event:

Previous editions of the Data Science in Aviation event were hosted in Madrid 2013, Paris 2014 and Brussels 2015. The popular event usually draws attendance from more than 80 individuals from top European and worldwide aviation entities (including Airbus, Eurocontrol, Boeing, EASA, Airlines, Airports, ANSPs, SESAR , Universities, etc) along with ICT and data-related entities (including CERN researchers, Fraunhofer, Infrastructure-related, and various universities). Notable presenters from the 2016 edition included EASA, Innaxis, NATS, Eurocontrol, Boeing, ENAC and Fraunhofer.

In terms of the event agenda and content, the presentations has traditionally outlined how data science is understood as a useful set of fundamental principles that support and guide the principled extraction of information and knowledge from aviation data. Furthermore, the discipline leans on well-known data-mining techniques, and goes far beyond these techniques with successful data-science paradigms which provide specific applications in various air transport areas (safety, performance, mobility etc).

 

On DATASET2050 Samuel’s presentation:

The event also highlighted a key presentation from Innaxis project coordinator, Samuel Cristobal. Samuel presented five different points on data science in aviation.

  • First, he explained how some of the data science tools, techniques and concepts have been used in the mobility context, specifically using the DATASET2050 project as a case example.
  • Second, Samuel explained the different door to door phases under analysis (door-kerb; kerb-gate; gate-gate; kerb-door), which helps to delve deeper in the different data science components within aviation phases.
  • Third, Samuel outlined the different links between project objectives and overall Flightpath2050 goals.
  • The fourth point explored mobility data in Europe, and the value of the DATASET approach in this context.
  • The presentation concluded with a fifth and final point announcing the next communication actions. The full presentation can be accessed here: https://www.dropbox.com/s/91julyl8gsij2k9/DATASET_SC_v1.pdf?dl=0

 

In sum, the fourth edition of the Data Science in Aviation event was an excellent opportunity for dissemination of DATASET2050. This was in conjunction with a fruitful exchange of ideas with other aviation data scientists, some of whom working with similar tools in other sub-areas far from mobility. We hope to continue this momentum of knowledge exchange and look forward to a potential fifth edition of the popular event.

 

You can watch DATASET2050 Samuel’s presentation here, and the rest of the event videos at Innaxis’ Vimeo channel.

Mobility presentation at Data Science In Aviation workshop (EASA, 2016)

The annual event exploring Data Science in Aviation (ComplexWorld funded; organized by Innaxis) has recently celebrated its fourth edition this past September 8th 2016. The event was hosted on the EASA premises in Cologne, Germany . This year it highlighted a presentation of the DATASET2050 project, “Data Science for Mobility”, by project coordinator Samuel Cristobal (Innaxis).

 

 

On the Data Science In Aviation event:

Previous editions of the Data Science in Aviation event were hosted in Madrid 2013, Paris 2014 and Brussels 2015. The popular event usually draws attendance from more than 80 individuals from top European and worldwide aviation entities (including Airbus, Eurocontrol, Boeing, EASA, Airlines, Airports, ANSPs, SESAR , Universities, etc) along with ICT and data-related entities (including CERN researchers, Fraunhofer, Infrastructure-related, and various universities). Notable presenters from the 2016 edition included EASA, Innaxis, NATS, Eurocontrol, Boeing, ENAC and Fraunhofer.

In terms of the event agenda and content, the presentations has traditionally outlined how data science is understood as a useful set of fundamental principles that support and guide the principled extraction of information and knowledge from aviation data. Furthermore, the discipline leans on well-known data-mining techniques, and goes far beyond these techniques with successful data-science paradigms which provide specific applications in various air transport areas (safety, performance, mobility etc).

 

On DATASET2050 Samuel’s presentation:

The event also highlighted a key presentation from Innaxis project coordinator, Samuel Cristobal. Samuel presented five different points on data science in aviation.

  • First, he explained how some of the data science tools, techniques and concepts have been used in the mobility context, specifically using the DATASET2050 project as a case example.
  • Second, Samuel explained the different door to door phases under analysis (door-kerb; kerb-gate; gate-gate; kerb-door), which helps to delve deeper in the different data science components within aviation phases.
  • Third, Samuel outlined the different links between project objectives and overall Flightpath2050 goals.
  • The fourth point explored mobility data in Europe, and the value of the DATASET approach in this context.
  • The presentation concluded with a fifth and final point announcing the next communication actions. The full presentation can be accessed here: https://www.dropbox.com/s/91julyl8gsij2k9/DATASET_SC_v1.pdf?dl=0

 

In sum, the fourth edition of the Data Science in Aviation event was an excellent opportunity for dissemination of DATASET2050. This was in conjunction with a fruitful exchange of ideas with other aviation data scientists, some of whom working with similar tools in other sub-areas far from mobility. We hope to continue this momentum of knowledge exchange and look forward to a potential fifth edition of the popular event.

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