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AI Driving Olympics + Q&A
Andrea Censi · Liam Paull · Jacopo Tani · Emilio Frazzoli · Holger Caesar · Matthew Walter · Andrea Daniele · Sahika Genc · Sharada Mohanty

Fri Dec 10 03:25 AM -- 03:45 AM (PST) @
in Competition Track Day 4: Overviews + Breakout Sessions »
Event URL: https://driving-olympics.ai »

The AI Driving Olympics (AI-DO) is a series of embodied intelligence competitions in the field of autonomous vehicles. The overall objective of AI-DO is to provide accessible mechanisms for benchmarking progress in autonomy applied to the task of autonomous driving. This edition of the AI-DO features three different leagues: (a) urban driving, based on the Duckietown platform; (b) advanced perception, based on the Motional nuScenes dataset; and (c) racing, based on the AWS Deepracer platform. Each league has several “challenges" with independent leaderboards. The urban driving and racing leagues include embodied tasks, where agents are deployed on physical robots in addition to simulation.

Author Information

Andrea Censi (ETH Zurich and nuTonomy inc.)
Liam Paull (Université de Montréal)
Jacopo Tani (ETH)
Emilio Frazzoli (ETHZ / nuTonomy)
Holger Caesar
Matthew Walter (TTI-Chicago)
Andrea Daniele (TTI-Chicago)
Sahika Genc (Amazon Artificial Intelligence)
Sharada Mohanty (AIcrowd SA)

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