A new test rig will blast real car sensors with spray from rotating wheels to see how well they cope in wet weather. This matters because water spray from other vehicles can blind both human drivers and the sensors that power Advanced Driver Assistance Systems (ADAS). For autonomous vehicles, the problem is worse: a sensor that misreads dense spray as a solid object could trigger unnecessary emergency braking, causing crashes. Understanding exactly how and when these systems fail in rain is a gap that must be filled before fully self-driving cars can operate safely on UK roads. If the research succeeds, it will give vehicle developers a standardised way to test sensor performance in realistic wet conditions. The second strand creates a digital database and two reference models for low-speed wind tunnels across the UK, allowing expensive aerodynamic data to be shared and compared. Together, these tools could shape how future autonomous vehicles are engineered to handle adverse weather—a quiet but critical piece of infrastructure for the transition to driverless transport.
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This research comprises two strands: the creation of a unique tire spray rig and a world leading experimental database of NWTF aerodynamic research data. The first strand will allow real sensors from road vehicle Advanced Driver Assistance Systems (ADAS) to be tested in water sprays from rotating car wheels. In wet conditions there can be a significant reduction in visibility caused by the spray from other vehicles. Whilst this is dangerous to the human driver, it can become critical for ADAS systems and could constrain the future operational use of full Autonomous Driving Systems. It is not only obscuration that is problematic, an ADAS sensor that 'imagines' a vehicle due to the density of spray and initiates emergency breaking could also cause unnecessary accidents. Understanding the limits of such systems in adverse weather conditions is vital in the development process so that appropriate mitigation actions can be taken. The Experimental Database strand creates a digital infrastructure to ensure that expensive and time-consuming aerodynamic tests can be fully exploited by the user community. It builds upon and complements the existing EPSRC NWTF network grant with the ambition of creating a world leading portal to access high quality aerodynamics data. It will also create two reference models and test across a number of UK low speed wind tunnels to assess their strengths and weaknesses.
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