Cameras are increasingly used in modern vehicles equipped with advanced driver assistance systems (ADAS) to collect environmental information. Cameras suffer performance degradation when driving in adverse weather conditions, such as rain, as precipitation droplets impact the camera lens and cause obstruction and blurring of the vision. The relationships between image quality, object detection accuracy, and surface wettability of camera lenses are investigated. This paper applies a previously developed evaluation procedure for wind tunnel testing with simulated adverse driving and rain conditions. Realistic rain characteristics perceived by a moving vehicle at different driving speeds are simulated using a novel rain simulation system implemented into a wind tunnel. Moreover, an emphasis is put on comparing the use of hydrophilic and hydrophobic surfaces to provide insights into material selection when designing camera lenses for ADAS. It is found that droplet dynamics, such as size, velocity, shape, and motion can impact the camera image quality and, subsequently, object detection accuracy. This paper demonstrates the use of various materials and evaluation metrics and their implications from a practical perspective when subjected to realistic driving-in-rain scenarios. The results suggest that the use of hydrophobic lenses promotes better performance over hydrophilic lenses in most cases with exceptions.
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