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Harsh weather conditions provide serious challenge for automated driving, since there is lack of experience in testing automated vehicles in such conditions. Vehicle automation is typically developed and tested for “normal” weather and road conditions, which is something that the ROADVIEW project will tackle on and find solutions for, by developing robust and co-efficient in-vehicle perception and systems.
The project aims for creating advanced environmental and traffic detection and prediction systems, with limiting false detection and paying special attention to vulnerable road users (VRUs). The solutions will significantly improve the detection in harsh weather conditions such as fog, rain, or snow. See the comprehensive work plan from the project’s official website.
FrostBit leads the development of test facility digital twins that include both controlled and real-world environments. The aim is to utilize the digital twins for state-of-the-art XiL (X-in-the-Loop) testing and the development of various perception sensor noise models.
In addition, FrostBit is also leading the annotation of the sensor data generated in the project. The labelling of perception sensor data e.g. LiDAR, RADAR and CAMERAS is required for machine learning models. FrostBit utilizes the Segments.AI platform (https://segments.ai/) for their labelling work.
ROADVIEW (Robust Automated Driving in Extreme Weather)
1.9.2022 – 31.8.2026
9,7 million €
Tuomas Herranen
ROADVIEW is an EU-funded Horizon Europe Project with 16 partners from 7 countries. The project mission is to increase the co-operated innovation, testing and demonstration objectives in theEuropean project field and establish fast development and introduction of automated mobility.