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Christopher Seubert

Ford Motor Company

Fouling Prevention for AV Sensors: Coatings, Cleaning, and Quantification


Autonomous vehicles (AVs) use a variety of sensors to perceive the vehicle’s surroundings. These sensors operate at different wavelengths and typically include cameras (visible), radar (microwave), LiDAR (infrared, light detection and ranging), and ultrasonic sensors. High transparency to the relevant radiation ranges is required for the optical elements of the sensors. Eventually, AVs will be operated in harsh conditions (rain, snow, dirt, etc.), and will be expected to function without interruption. Unfortunately, a definitive coatings and cleaning strategy to keep these sensors free of fouling agents is still under development.

In this talk, we focus on the characterization of transparent, functional coatings and their interactions with various foulants and cleaning protocols. In particular, we examine methods to reproducibly foul surfaces with dirt and de-icing salts, and subsequently clean those surfaces. The effects of accelerated weathering on the coatings’ performance are also examined to better understand the durability of these functional coatings and how changes in surface chemistry and morphology affect anti-fouling and easy-clean performance.


Christopher is a Research Engineer at Ford Motor Company’s Research and Innovation Center in Dearborn, Michigan. He received his bachelor’s degree from the University of Illinois and his M.S./Ph.D. from the University of Michigan, all in Materials Science & Engineering. Over the past 18 years, Chris has worked and published on a number of projects including UV/EB curable materials, scratch and mar behavior, paint durability, color measurement and modeling, as well as the scattering behavior of automotive paints and materials.