Mobility datasets exploration tool

Within the project, we have recently listed the sources of EU door-to-door mobility datasets, reports and papers. That information is crucial for us to build the subsequent data-driven tasks (including the model). On top of that, they could be extremely useful to anyone doing research or simply interested in the mobility topic.

Having this in mind, the consortium has developed a visual, interactive tool that provides all the information in a simple, attractive way.  By using a dynamic D3.js , it includes information about data sources together to their temporal data coverage, authors, description and availability

How it works? Click here: The datasets have been categorized in 9 families, all of them relevant within mobility context.

  • Demographic
  • Passenger demand
  • Passenger type
  • Passenger behaviour
  • Door-to-kerb
  • Kerb-to-gate
  • Gate-to-kerb
  • Airside capacity
  • Competing services

By clicking in each of them (the text, right side), all the data sources available within that family are displayed. Doing a mouseover on each of them (right side), detailed information is given in a tool tip about the data coverage, sources etc. In the cases too many sources are available, scrolling is the way to see them all 🙂 Clicking on the [x] at the top brings you back to the main page.




DATASET2050 presented at ACARE

DATASET2050 participation in ACARE WG1 Meeting (Brussels, June 3, 2015)

Bauhaus Luftfahrt actively participated in the Advisory Council for Aviation Research and Innovation in Europe (ACARE) Working Group 1 Meeting on June 3, 2015 in Brussels on behalf of DATASET2050. ACARE’s main task is to provide a network for strategic research in aeronautics and air transport and to identifying strategic directions for aviation research and industry. The members of ACARE are organised in five working groups: (1) Mobility, (2) Competitiveness, (3) Environment and Energy, (4) Safety and Security, and (5) Resources. Within the different working groups experts from industry, science and politics meet regularly to discuss and define key topics and to monitor progress regarding mobility and air transportation related research. Three partners of DATASET2050 are part of ACARE: Bauhaus, EUROCONTROL and Innaxis. Working Group 1, in particular, is concerned with the societal and market needs and how these can be met in the future. Main objectives of the meeting in Brussels on June 3 were an update on the identification of bottlenecks within the current transport system and the respective formulation of research needs. Furthermore, three current projects within the scope of WG1 were presented: DATASET2050, DORA, and PASSME.

The DORA project starting in June 2015 (“Door to Door Information for Air Passengers”) focuses on passenger door-to-door travel and the provision of an integrated information system along the entire journey. The goal of the PASSME (“Personalised Airport Systems for Seamless Mobility and Experience”) project is to reduce passenger travel time by 60 minutes by introducing novel solutions (up to TRL6). These may include systems to provide predictive analysis of passenger flows or redesigned airport and aircraft processes that speed up the passenger journey and add to a hassle-free travel experience. Although these two projects have a different focus, both are concerned with enhancing the passenger journey and addressing door-to-door travel. This yields potential for valuable future exchange between the different partners and for the different work packages in DATASET2050.

The presentation of DATASET2050 at this particular meeting mainly focused on the work scope of work package 3, passenger demand profile. The intention of WP3 is to understand in a better way the current as well as the future transport system from the user perspective. For this purpose, travel behaviour is depicted by collecting a range of data on passenger needs and expectations for different time horizons. As depicted in step 1 in the figure, this demand is derived from a range of data sources: First, macro data, such as information on demographics or income, is collected to obtain a broad basis for the differentiation of population groups (as addressed in Blog Post #5). To introduce a transport-specific focus, passenger travel behaviour is analysed by looking at modal shares, traffic patterns and flows, e.g. travel times and destinations, as well as the availability and constitution of airport access modes. The characteristics derived from macro and transport-specific data are complemented by specific passenger attributes. High affinity for technology, for example, can be one feature that characterizes a certain type of passenger. Passengers might also place high emphasis on individualized products such as customized meals or entertainment programs during a flight.


Approach towards the derivation of distinct passenger clusters and requirements

The data is used to define specific demand profiles, i.e. to differentiate between a variety of passenger groups beyond the traditional classification of business, leisure, and visiting friends and relatives (step 2 in the figure). For example, one group may be characterized by travellers in the age group 20 to 25 with a high affinity for state-of-the-art technology solutions, travelling on a low budget to visit both friends and families across different European cities.

For each defined passenger demand profile (“passenger clusters”) requirements for the current as well as future transport system (2035 and 2050) are defined (step 3 in figure). A specification resulting from such a cluster can be the provision of aligned travel information along the entire journey. This means that all involved transport providers share information on schedules and expected delays to provide passengers with dynamic real-time information. These current and future requirements are then used to identify bottlenecks within passenger door-to-door transport and to design approaches how these can be addressed within future transport systems.





Dynamics of European Demographics

The objective of WP3 within DATASET2050 is to understand the current and future transport system from the passengers perspective, in a more detailed and thorough way than currently available. As a first step, it is necessary to better grasp passengers’ expectations, needs and requirements and their specific travel behaviour. In this context, population, and most importantly demography evolution, plays a crucial role in terms of current transport flows. Transport flows will obviously be derived from where do people live in Europe. As a general rule, fertility rate and emigration/immigration due to [un]employment levels are for the most cases the key drivers of European demographics.

Based on data from the German Federal Office for Building and Regional Planning, it has been published some days ago an interesting article on the European demographics. This article has been considered worth including in the monthly blogpost, given the synergies with the current research being performed within DATASET2050. Some general conclusions extracted from the analyses done in the article (and shown in the picture below) are the following:

  • European city suburbs have attracted new inhabitants coming both from the crowded city centres and from other surrounding (and further) rural areas
  • Both in Germany and in Poland, the trend is moving from the East to West, which clearly corresponds to the evolution of the employment levels at those areas.
  • Similar situation in Italy, where the south-north trend difference is remarkable
  • France population is growing, especially rapid in coastal areas. Population growth is quite homogeneous, given the good transport system available at country and local levels
  • In Spain, population growth is notable around Madrid, Barcelona and the coast. Population is decreasing in the north-west area of Spain and in Portugal
  • Easter Europe and the Baltic states have shrunk dramatically

Several maps and explanations zooming in different countries and cities are available at the original source.  Areas coloured green had an average annual increase in population over the 2001-2011 time span, and areas coloured brown experienced a decline in population. In areas coloured white, no significant change occurred.

enjoy it!


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