End-to-end Autonomous Driving in Heterogeneous Traffic Scenario Using Deep Reinforcement Learning
In this paper, we propose an end-to-end autonomous driving architecture for safe maneuvering in heterogeneous traffic using a reinforcement learning (RL) algorithm. Using the proposed architecture we develop an RL agent …