ApolloRL: a Reinforcement Learning Platform for Autonomous Driving
Baidu Apollo Autonomous Driving（百度阿波罗自动驾驶）；University of Cambridge（剑桥大学）
英文摘要：
We introduce ApolloRL, an open platform for research in reinforcement learning for autonomous driving. The platform provides a complete closed-loop pipeline with training, simulation, and evaluation components. It comes with 300 hours of real-world data in driving scenarios and popular baselines such as Proximal Policy Optimization (PPO) and Soft Actor-Critic (SAC) agents. We elaborate in this paper on the architecture and the environment defined in the platform. In addition, we discuss the performance of the baseline agents in the ApolloRL environment.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
