Using floating car data for more precise road weather forecasts

Meike Hellweg, John-Walter Acevedo-Valencia, Zoi Paschalidi, Jens Nachtigall, Thomas Kratzsch, Christoph Stiller

Abstract: To increase the spatial and temporal resolution of weather forecasts and thereby ensure safe autonomous driving functions, a denser network of measurements is necessary. This paper presents the project Fleet Weather Map, which investigates the potential of using floating car data as a source for meteorological data. Furthermore, the need for bias corrections and quality control of the raw signals is shown. The potential of the approach used gives first promising results and aims for increasing the forecast step width to 5 minutes.