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Passenger-centric Big Data Sources for Socio-economic and Behavioural Research in ATM

Objective

The Flightpath 2050 report envisages a passenger-centric air transport system thoroughly integrated with other transport modes, with the goal of taking travellers from door to door predictably and efficiently. However, ATM operations have so far lacked a passenger-oriented perspective, with performance objectives not necessarily taking into account the ultimate consequences for the passenger. There is a lack of understanding of the impact of passengers’ behaviour on ATM and vice versa. Research in this area has so far been constrained by the limited availability of behavioural data. The pervasive penetration of smart devices in our daily lives and the emergence of big data analytics open new opportunities to overcome this situation: for the first time, we have large-scale dynamic data allowing us to test hypotheses about travellers’ behaviour. The goal of BigData4ATM is to investigate how these data can be analysed and combined with more traditional demographic, economic and air transport databases to extract relevant information about passengers’ behaviour and use this information to inform ATM decision making processes. The specific objectives of the project are:
1. to integrate and analyse multiple sources of passenger-centric spatio-temporal data (mobile phone records, data from geolocation apps, credit card records, etc.) with the aim of eliciting passengers’ behavioural patterns;
2. to develop new theoretical models translating these behavioural patterns into relevant and actionable indicators for the planning and management of the ATM system;
3. to evaluate the potential applications of the new data sources, data analytics techniques and theoretical models through a number of case studies, including the development of passenger-centric door-to-door delay metrics, the improvement of air traffic forecasting models, the analysis of intra-airport passenger behaviour and its impact on ATM, and the assessment of the socio-economic impact of ATM disruptions.

Field of science

  • /natural sciences/computer and information sciences/databases
  • /engineering and technology/electrical engineering, electronic engineering, information engineering/information engineering/telecommunications/mobile phone
  • /social sciences/social and economic geography/transport
  • /natural sciences/computer and information sciences/data science/big data
  • /natural sciences/computer and information sciences/data science/data analysis

Call for proposal

H2020-SESAR-2015-1
See other projects for this call

Funding Scheme

SESAR-RIA - Research and Innovation action

Coordinator

NOMMON SOLUTIONS AND TECHNOLOGIES SL
Address
Calle Claudio Coello 124 - Planta 4A Trasera
28006 Madrid
Spain
Activity type
Private for-profit entities (excluding Higher or Secondary Education Establishments)
EU contribution
€ 233 187,50

Participants (4)

UNIVERSITAT DE LES ILLES BALEARS
Spain
EU contribution
€ 128 000
Address
Carretera De Valldemossa Km 7.5
07122 Palma De Mallorca
Activity type
Higher or Secondary Education Establishments
FRAUNHOFER GESELLSCHAFT ZUR FOERDERUNG DER ANGEWANDTEN FORSCHUNG E.V.
Germany
EU contribution
€ 92 577,50
Address
Hansastrasse 27C
80686 Munchen
Activity type
Research Organisations
THE HEBREW UNIVERSITY OF JERUSALEM
Israel
EU contribution
€ 47 375
Address
Edmond J Safra Campus Givat Ram
91904 Jerusalem
Activity type
Higher or Secondary Education Establishments
INGENIERIA DE SISTEMAS PARA LA DEFENSA DE ESPANA SA-SME MP
Spain
EU contribution
€ 98 592,50
Address
Calle Beatriz De Bobadilla 3
28040 Madrid
Activity type
Private for-profit entities (excluding Higher or Secondary Education Establishments)