mlsanityData to 14 Oct 2026

Systematic Analyses of Reinforcement Learning Controllers in Signalized Urban Corridors

arXiv 2604.02025 ↗First posted 2 Apr 2026cs.AI cs.LG cs.MAcited by 0

On the map: Deep reinforcement learning methods → RL for autonomous driving and traffic

Abstract (arXiv)

In this work, we extend our systematic capacity region perspective to multi-junction traffic networks, focussing on the special case of an urban corridor network. In particular, we train and evaluate centralized, fully decentralized, and parameter-sharing decentralized RL controllers, and compare their capacity regions and ATTs together with a classical baseline MaxPressure controller. Further, we show how the parametersharing controller may be generalised to be deployed on a larger network than it was originally trained on. In this setting, we show some initial findings that suggest that even though the junctions are not formally coordinated, traffic may self organise into `green waves'.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Placed in RL for autonomous driving and traffic, one of 15 directions in Deep reinforcement learning methods. Builds on 3 of its 7 references that are in the map. First posted on arXiv 2 Apr 2026.

Builds on

3 of 7 references.

References · 3

  1. 2017Proximal Policy Optimization Algorithmscited by 15,215
  2. 2021The Surprising Effectiveness of PPO in Cooperative, Multi-Agent Gamescited by 942
  3. 2019A Survey on Traffic Signal Control Methodscited by 79

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  3. 2025Robust Single-Agent Reinforcement Learning for Regional Traffic Signal Control Under Demand Fluctuations
  4. 2025Large-Scale Mixed-Traffic and Intersection Control using Multi-agent Reinforcement Learning
  5. 2025Unicorn: A Universal and Collaborative Reinforcement Learning Approach Towards Generalizable Network-Wide Traffic Signal Control
  6. 2024Reinforcement Learning for Adaptive Traffic Signal Control: Turn-Based and Time-Based Approaches to Reduce Congestion
  7. 2025Distributionally Robust Multi-Agent Reinforcement Learning for Intelligent Traffic Control ↗
  8. 2024Neighbor-Aware Reinforcement Learning for Mixed Traffic Optimization in Large-scale Networks