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Modular Learning for Mixed Autonomy Traffic by Bora Cobanoglu is a document available to read on EtoBox.

What is Modular Learning for Mixed Autonomy Traffic about?

1. The document proposes a modular learning framework called Flow that leverages deep reinforcement learning methods to address complex traffic dynamics arising from the partial adoption of autonomous vehicles. 2. Flow consists of reusable modules that capture common traffic phenomena like traffic jams and lane changing. Learned control laws using Flow were found to exceed human driving performance by at least 40% with only 5-10% adoption of autonomous vehicles. 3. In tests of partially observed single-

Author

Bora Cobanoglu

Language

EN