Material characterization and innovative strategies for enhancing the performance of autonomous vehicle sensors in adverse weather

Autonomous vehicles (AVs) will potentially revolutionize the transportation sector. The value proposition of AVs includes improved road safety, increased traffic efficiency, reduced number of accidents, and decreased emissions. AVs heavily rely on the input of various sensors (Optical, Radar, Lidar, etc.) to capture environmental and traffic data. Clear sensor vision under all vehicle operating conditions has to be ensured to guarantee safe and uninterrupted operations of the vehicle. Vision sensors, such as cameras and lidar need an unobstructed optical view for performance. Different packaging and design requirements may require sensors to be applied in areas prone to soiling and contamination (e.g., rain, snow, spray, dust, etc.) Measures need to be taken to promote and ensure a robust and reliable sensor performance in all environmental conditions. This project proposes to perform material characterization and develop innovative sensor soiling mitigation strategies for autonomous vehicle applications in adverse weather.

Faculty Supervisor:

Martin Agelin-Chaab;Langis Roy

Student:

Partner:

Magna Exteriors

Discipline:

Engineering

Sector:

Manufacturing

University:

University of Ontario Institute of Technology

Program: