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Deep RL for Autonomous Driving in CARLA by ozr72121 is a document available to read on EtoBox.

What is Deep RL for Autonomous Driving in CARLA about?

This document discusses using deep reinforcement learning to develop autonomous vehicle navigation policies in the CARLA simulation environment. Specifically, it aims to discover a method for an autonomous car to maintain its lane at high speeds while avoiding collisions with other vehicles. The document provides background on autonomous driving and reinforcement learning, reviews related work applying deep RL to navigation tasks, and formulates the lane-keeping problem as a Markov Decision Process to apply

Author

ozr72121

Language

EN