TorchDriveEnv: A Reinforcement Learning Benchmark for Autonomous Driving with Reactive, Realistic, and Diverse Non-Playable Characters

arXiv:2405.04491v1 Announce Type: cross
Abstract: The training, testing, and deployment, of autonomous vehicles requires realistic and efficient simulators. Moreover, because of the high variability between different problems presented in different autonomous systems, these simulators need to be easy to use, and easy to modify. To address these problems we introduce TorchDriveSim and its benchmark extension TorchDriveEnv. TorchDriveEnv is a lightweight reinforcement learning benchmark programmed entirely in Python, which can be modified to test a number of different factors in learned …

abstract arxiv autonomous autonomous driving autonomous systems autonomous vehicles benchmark characters cs.ai cs.lg cs.ma cs.ro deployment diverse driving easy reinforcement reinforcement learning systems testing training type vehicles