Nanocoatings Testing for Improved Perception in Adverse Weather Autonomous Driving

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Robust perception in harsh weather conditions is one of the biggest technical hurdles preventing the widespread deployment of autonomous vehicles, particularly in northern climates. The Autonomoose self-driving car program at the University of Waterloo has been working on autonomous perception capabilities for self-driving cars in adverse weather for the last three years, and is a leader in the areas of vision and lidar processing to remove the effects of weather. The industrial partner, Alchemy, is currently evaluating the use of low energy coatings to improve autonomous vehicle sensors (LiDAR and Camera) performance in heavy rain/snow conditions, as well as repelling debris such as bird droppings, salt rings, and insects. This project will apply the Alchemy coating to the Autonomoose test vehicle, and evaluate benchmark performance of vision and lidar processing algorithms with and without the coatings in adverse weather. The project will focus on both rain and snow conditions, weather permitting, and could lead to a significant reduction in the time to release of winter-ready self-driving cars in Canada, and to a central position for Alchemy in the international self-driving car sensor manufacturing market.