AutonoWeather: Enabling autonomous driving in winter conditions through optimized road weather interpretation and forecast
The goal of the study is to reduce road fatalities by making autonomous systems more capable at operating in winter circumstances, such as found in Norway.
Objectives: The current generation autonomous systems do not contain the intelligence that is required to recognize slippery roads. The primary objective of the proposed study is to develop an accurate and affordable method for road-friction estimation in real-time. Such estimates are established using a novel combination of road weather models and car-mounted environmental sensors. Finally, the developed methods allow for more efficient road maintenance, which can significantly reduce the use of harmful salts and chemicals.
Background: The AutonoWeather project aims to develop the worlds first in-situ road friction estimate using a dedicated on-board meteorological sensor suite. A successful outcome of the project shall provide a cheap and accessible way to better inform the driver and the cars on-board systems on the occurring road surface conditions directly under the car. This is a unique capability that is not yet available to society. The expected research results can enable a reduction in potentially fatal accidents that result from an incorrect application of autonomous driving systems. These benefits are particularly true for colder climates, such as found in Norway.
Owner of the project: NORCE Norwegian Research Centre
Participants: Universitetet i Oslo, by Svein-Erik Hamran (research activity), IFE (Research activity),Tracsense AS (research and financing)
Financing: Financial support was kindly provided by the Research Council of Norway and University of Oslo through the research project AutonoWeather (no. 301575)