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Robust Automated Driving in Extreme Weather – ROADVIEW

Robust Automated Driving in Extreme Weather – ROADVIEW

Professor Valentina Donzella, WMG

This €850,000 project, led at WMG by Professor Valentina Donzella, entails designing, implementing, and demonstrating how self-driving automated vehicles can drive safely and robustly in harsh weather conditions, such as rain, fog, and snow.

The €9,700,000 EU Horizon project is led by Halmstad University and features cooperation with 15 partners in the field, including research institutes, high-tech SMEs and industry leaders, such as Ford Otosan and Konrad Technologies.

Find out more about Professor Valentina's and Intelligent Vehicles (IV) Sensors research.

ROADVIEW aims to develop robust and cost-efficient in-vehicle perception and decision-making systems for connected and automated vehicles with enhanced sensing performance under harsh weather conditions and different traffic scenarios. Harsh weather challenges are a severe technological barrier for automated vehicles. More information on the project can be found here.

The IV Sensors group is leading the work package around validated sensor noise models for synthetic environment and X-i-L. Furthermore, the group is developing and validating physics based weather models affecting perception sensors and continuing the work on identifying noise and compounding noise factors. Finally, the group is also co-leading the X-i-L work package, supporting the integration of the developed models for X-in-the-Loop testing.