NWO Commit2Data grant for geometric algorithms research in smart mobility
Probe data from vehicles captures traffic and traffic flow. The corresponding GPS-based trajectories allow various types of analyses, but especially the combination with other data like vehicle-based LiDAR or weather data opens up new possibilities in data correction, pattern detection, and visualization. Both the volume and the heterogeneity of the data poses challenges that need to be addressed, to advance data quality, efficiency, and analysis in automotive high-tech systems, smart cities, and smart logistics.
To tackle these challenges, prof.dr. Bettina Speckmann, dr. Kevin Verbeek and dr. Wouter Meulemans (Applied Geometric Algorithms group at TU Eindhoven) and prof.dr. Marc van Kreveld and dr. Maarten Löffler (Utrecht University) join forces with industry partners HERE and Fugro and public partner NDW (Nationale Databank Wegverkeersgegevens).
This consortium was awarded a cross-cutting Commit2Data grant by NWO which funds 2 PhD students and 1 postdoc. The aim of the project is to develop and extend foundational geometric-algorithmic techniques to overcome challenges posed by heterogeneous (traffic) data. Particular emphasis lies on models for spatiotemporal data quality (e.g. outlier detection, data completion, metadata provision), automated pattern detection and analysis of heterogeneous data (combining e.g. GPS trajectories with road networks, weather information, visibility, land cover, etc.), and information visualization within 3D environments, with a particular emphasis on traffic flow.