Suggested by: Martin Loidl
Short description: The city of Salzburg extended the network of permanent bicycle counting stations to a total of over 20. The initial idea was to create an evidence base for monitoring bicycle traffic at a city level. However, there are some unresolved methodological issues, such as how point measurements can serve as indicators for the distribution of flows in a road network. Besides this, there is a lack of concrete use cases, which could demonstrate the benefit of such a sensor network.
Research for this master thesis should address one or more of the following topics (but is not limited to):
- Definition of use cases in the context of planning, monitoring and communication.
- Methodological advancements with a special focus on the relation of flows and point measurements.
- Spatio-temporal analysis of counting data in relation to additional data sources (such as weather data).
- Visualization and exploration of data in near real-time (for instance in a dashboard).
References, suggested reading:
- ROMANILLOS, G., ZALTZ AUSTWICK, M., ETTEMA, D. & DE KRUIJF, J. 2016. Big Data and Cycling. Transport Reviews, 36, 114-133.
- LOIDL, M. 2020, (Geo-) Daten für ein besseres Verständnis von Fahrradmobilität. online Lecture at TU Vienna https://youtu.be/W8LueQE8sc8 (in German language)
- LOIDL, M. 2020, Cycling Data. https://gicycle.wordpress.com/2020/05/15/cycling-data/
Start/finish: anytime
Prerequisites/qualifications: Profound skills in data modelling and processing. Scripting, database and spatial analytics (network analysis) skills.
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