predictive analytics

Detecting probability of ice formation on overhead lines of the Dutch railway network

Ice formation along the overhead lines is a potential source of infrastructure failure and transportation disruption. Modelling ice formation over structures is challenging because it may occur at a very local scale, often far away from measuring stations. Experts in the field have empirically defined models of ice accretion under laboratory conditions. However, the significant number and complexity of the geophysical parameters included in these models, poses major hurdles for their application at the national level.

Gridding station-based wind observations

The European Climate Assessment & Dataset (ECA&D) collects high-quality observational datasets provided by 60+ participant countries. One of the products this organization provides is the E-OBS daily gridded observational dataset, which facilitates the access of the general public to long-term (1950-present) weather gridded layers. The latest release of E-OBS (v20.0) provides data in regular grids for temperature, precipitation, mean sea level pressure and global radiation (newest!), which enable the assessment and analysis of observed changes in climate extremes in Europe.

Identifying risky locations for road accidents due to crosswind

Crosswind is a potential source of road accidents, especially for unloaded trucks. We joined forces with colleagues from the ILT and RWS datalabs to assess how feasible it is to build predictive models capable of identifying risky locations for truck accidents. In this way, it is possible to proactively plan traffic inspections that might reduce the probability of accidents. Data analysis We combined a given set of locations of truck accidents with road characteristics, traffic intensity, and weather variables.