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Overview of the competition

Modified 2018-06-17 by Andrea Censi

What are the AI Driving Olympics? The AI Driving Olympics (AIDO) are a set of 5 challenges designed to exemplify the unique characteristics of data science in the context of autonomous driving.

To understand how to solve a robotics challenge, we will explore the various dimensions of performance and difficulties involved.

Overview of tasks

Modified 2018-06-17 by Andrea Censi

Lane following
Lane following+v
Navigation+v
Fleet management
AMOD coordination

The AI Driving Olympics competition is structured into the following five separate tasks:

Embodied individual robot tasks: Tasks within which code to control a single Duckiebot is submitted. * Lane following: Control of a Duckiebot to drive on the right lane on streets within Duckietown without other moving Duckiebots present. * Lane following + vehicles: Control of a Duckiebot to drive on the right lane on streets within Duckietown with other moving Duckiebots present. * Navigation + vehicles: Navigation task of a Duckiebot to drive from point $A$ to point $B$ within Duckietown while following the rules of the road and while other Duckiebots are likewise driving in the road. Fleet-level social tasks: Tasks within which code to control multiple robots or agents is submitted while lower-level functions are already provided. * Fleet management: Task to control a small fleet of Duckiebots within Duckietown to pick up a set of virtual customers and drive them to a destination point. * Autonomous Mobility-on-Demand: Task to control the movement of a fleet of autonomous vehicles in a simulated city to pick up customers and drive them to their destinations.

Participants may submit code to each challenge individually. Tasks proposed in the AI Driving Olympics are ordered first by type and secondly by increasing difficulty in a way which encourages modular reuse of solutions to previous tasks.

Because of mathjax bug

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