Quantifying Sensor Surface Contamination for Safe Vehicle Automation (QonSense)

The core issue is ensuring sensor reliability in various environments, crucial for road safety and sustainability per the FFI Safe Automated Driving subprogram’s mission. Aligned with the FFI roadmap, enhancing road safety and sustainable transport via safe connected automated vehicles, this project aims to quantify the impact of sensor surface contamination on signal performance. Achieving this goal directly contributes to the sub-program’s focus on vehicle perception, situational awareness, and efficient automated functionality development.

This research will promote safer roads and vehicle use by preventing sensor malfunctions due to contamination. Beneficiaries include the automotive industry, facilitating earlier development of robust ADAS and AD systems in the design process, and society as a whole, benefiting from improved road safety. Specifically, the project will analyze and quantify liquid and particulate accumulations on radar, ultrasonic, and lidar sensors, assessing their subsequent effects on sensor functionality. These analyses will occur in static (anechoic chamber), dynamic (wind tunnel), and in-field testing.

Halmstad University oversees the application process and project coordination while offering expertise in radar target simulation, signal analysis, and advanced radar testing facilities/methods. Volvo Cars contributes industrial input and expertise in sensor technology, automotive engineering, wind tunnel testing methodologies, and vehicle test platforms.