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All-weather autonomous vehicle operation poses significant challenges,encompassing modules from perception and decision-making to path planning andcontrol. The complexity arises from the need to address adverse weatherconditions such as rain, snow, and fog across the autonomy stack. Conventionalmodel-based single-module approaches often lack holistic integration withupstream or downstream tasks. We tackle this problem by proposing amulti-module and modular system architecture with considerations for adverseweather across the perception level, through features such as snow covered curbdetection, to decision-making and safety monitoring. Through daily weekdayservice on the WATonoBus platform for almost two years, we demonstrate that ourproposed approach is capable of addressing adverse weather conditions andprovide valuable insights from edge cases observed during operation.

WATonoBus: Field-Tested All-Weather Autonomous Shuttle Technology