UV-durable self-cleaning coatings for autonomous driving

Abstract A key technology to ensure the safety and accuracy of autonomous driving for future transportation is the cleanliness of the sensor surfaces for accurate signal reading. This study focuses on hydrophobic coatings with self-cleaning performances and UV durability, their possible degradation mechanism of static water contact angle (sWCA), and the effect of the hydrophobic surface on camera image quality. The UV-durable hydrophobic coatings are applied by a spray process followed by a thermal curing. The UV-durable hydrophobic coatings are evaluated on a vision camera under lab-simulated weathering conditions such as rain, mud, fog, and bugs, on samples as-prepared and after various hours of Weather-Ometer® weathering. The results indicate that the sWCA degradation of the UV-durable hydrophobic coatings during accelerated weathering is corresponding to the loss of fluorine (F) atomic percentage in the coatings, and the vision camera imaging quality improves significantly with the UV-durable hydrophobic coatings in comparison to an uncoated surface. The self-cleaning performances of the UV-durable hydrophobic coatings, as measured by two metrics using signal-to-noise ratio and modulation transfer function 50 loss (MTF50 loss ), linearly correlate with sWCA of the coatings. The UV-durable hydrophobic coatings on the sensor surface will significantly benefit autonomous driving specifically for accurate signal reading under inclement weather.