The availability of big data from various sources is becoming increasingly important in the mobility domain. Understanding all this data correctly and using it to arrive at knowledge, relevant to users, is crucial. Therefore, we focus on understanding how users behave and what their needs are. This knowledge is translated into innovative and tangible solutions and products. Our mobility research focuses on three major research themes.

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Data collection

Data collection on travel behaviour includes all activities related to data collection and the use of technologies to collect travel behaviour and trip data: from collecting and analysing activity diaries to big data, crowdsourcing, tracking and tracing in real time, targeting niche groups (e.g. children, the elderly, people with care needs).

Principle investigators: An Neven, Bruno Kochan, Ansar Yasar, Tom Bellemans, Davy Janssens, Elke Hermans, Wim Ectors

Research topics:

  • Development and analysis of travel behaviour studies and sequential activity diary data;
  • Development of stated preference and stated choice studies (looking at responses to e.g. "what-if" scenarios);
  • Capture big data (mobile phone, GPS, drones) and annotate/enrich this data with behavioural info;
  • Engage general public (crowdsourcing) and encourage citizen science in transport;
  • Tracking people in real-time via wearable sensors and mobile apps;
  • Capture data from niche groups in travel and tourism research (e.g. children, care needs).
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Data analysis

Once the data is available, real knowledge must be created from the raw data via stated preference and stated choice models, Activity Based models, Artificial Intelligence solutions and deep learning algorithms...

Principle investigators: Tom Bellemans, Bruno Kochan, Muhammad Adnan, Wim Ectors

Research topics:

  • Developing stated preference and stated choice models to make future predictions;
  • Building activity-based and agent-based models to capture complex interactions and joint activities;
  • Optimising computer resources and scalability for advanced data analytics within acceptable run times;
  • Develop AI solutions and deep learning algorithms to extract knowledge from (video) images.
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Solution-oriented research

To change, adapt or stear human behaviour, we strive to work out technological solutions. In this research area, we already have clear applications in mind, aiming to solve or improve an existing situation (via anti-post evaluations, development of learning platforms & smart solutions, intelligent routing algorithms...).

Principle investigators: An Neven, Tom Bellemans, Bruno Kochan, Ansar Yasar, Muhammad Adnan, Wim Ectors, Davy Janssens, Yves Vanrompay

Research topics:

  • Pre- and post-evaluations to determine the role of intervention strategies;
  • Develop learning platforms, awareness campaigns and other strategies to change human behaviour (e.g. software, apps);
  • Developing smart solutions using open data and using and adapting existing technical platforms and resources for this purpose;
  • Extending intelligent routing algorithms for complex route choice analysis to provide route recommendations to end users;
  • Visualise geographical (time-space) info and use and automate existing map matching and geocoding services.

We are looking for participants for scientific studies

Apply to participate in scientific studies on transportation & road safety!

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Do you have a question or would you like to collaborate with IMOB?

Then don't hesitate to contact us. We are available every weekday from 9 a.m. to 5 p.m.

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