Safe Reinforcement Learning with Scene Decomposition for Navigating Complex Urban Environments [article]

Maxime Bouton, Alireza Nakhaei, Kikuo Fujimura, Mykel J. Kochenderfer
2019 arXiv   pre-print
Navigating urban environments represents a complex task for automated vehicles. They must reach their goal safely and efficiently while considering a multitude of traffic participants. We propose a modular decision making algorithm to autonomously navigate intersections, addressing challenges of existing rule-based and reinforcement learning (RL) approaches. We first present a safe RL algorithm relying on a model-checker to ensure safety guarantees. To make the decision strategy robust to
more » ... tion errors and occlusions, we introduce a belief update technique using a learning based approach. Finally, we use a scene decomposition approach to scale our algorithm to environments with multiple traffic participants. We empirically demonstrate that our algorithm outperforms rule-based methods and reinforcement learning techniques on a complex intersection scenario.
arXiv:1904.11483v1 fatcat:niiykwcshfbbpeahvfflqmttpy