WATonoBus: An All Weather Autonomous Shuttle

Bhatt, Neel P., Zhang, Ruihe, Ning, Minghao, Alghooneh, Ahmad Reza, Sun, Joseph, Panahandeh, Pouya, Mohammadbagher, Ehsan, Ecclestone, Ted, MacCallum, Ben, Hashemi, Ehsan, Khajepour, Amir

arXiv.org Artificial Intelligence 

Autonomous vehicle all-weather operation poses significant challenges, encompassing modules from perception and decision-making to path planning and control. The complexity arises from the need to address adverse weather conditions like rain, snow, and fog across the autonomy stack. Conventional model-based and single-module approaches often lack holistic integration with upstream or downstream tasks. We tackle this problem by proposing a multi-module and modular system architecture with considerations for adverse weather across the perception level, through features such as snow covered curb detection, to decision-making and safety monitoring. Through daily weekday service on the WATonoBus platform for almost a year, we demonstrate that our proposed approach is capable of addressing adverse weather conditions and provide valuable learning from edge cases observed during operation.