SUMO

The SUMO dataset/benchmark is a traffic simulator used to evaluate reinforcement learning algorithms in heterogeneous environments, specifically in the context of autonomous driving scenarios.

Papers using SUMO (3)

PALCAS: A Priority-Aware Intelligent Lane Change Advisory System for Autonomous Vehicles using Federated Reinforcement Learning2026The Actor-Critic Update Order Matters for PPO in Federated Reinforcement Learning2025Realistic Urban Traffic Generator using Decentralized Federated Learning for the SUMO simulator2025