MetaDrive: Composing Diverse Driving Scenarios for Generalizable Reinforcement Learning
MetaDrive: Composing Diverse Driving Scenarios for Generalizable Reinforcement Learning
Driving safely requires multiple capabilities from human and intelligent agents, such as the generalizability to unseen environments, the safety awareness of the surrounding traffic, and the decision-making in complex multi-agent settings. Despite the great success of Reinforcement Learning (RL), most of the RL research works investigate each capability separately due …