mlsanityData to 14 Oct 2026

A Distributed Approach to Autonomous Intersection Management via Multi-Agent Reinforcement Learning

arXiv 2405.08655 ↗First posted 14 May 2024cs.RO cs.AIcited by 1

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Abstract (arXiv)

Autonomous intersection management (AIM) poses significant challenges due to the intricate nature of real-world traffic scenarios and the need for a highly expensive centralised server in charge of simultaneously controlling all the vehicles. This study addresses such issues by proposing a novel distributed approach to AIM utilizing multi-agent reinforcement learning (MARL). We show that by leveraging the 3D surround view technology for advanced assistance systems, autonomous vehicles can accurately navigate intersection scenarios without needing any centralised controller. The contributions of this paper thus include a MARL-based algorithm for the autonomous management of a 4-way intersection and also the introduction of a new strategy called prioritised scenario replay for improved training efficacy. We validate our approach as an innovative alternative to conventional centralised AIM techniques, ensuring the full reproducibility of our results. Specifically, experiments conducted in virtual environments using the SMARTS platform highlight its superiority over benchmarks across various metrics.

Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 12 of its 45 references that are in the map. First posted on arXiv 14 May 2024.

Builds on

12 of 45 references.

References · 12

  1. 2015Deep Reinforcement Learning with Double Q-learningcited by 1,745
  2. 2015Prioritized Experience Replaycited by 1,099
  3. 2015Dueling Network Architectures for Deep Reinforcement Learningcited by 785
  4. 2017Flow: A Modular Learning Framework for Mixed Autonomy Trafficcited by 73
  5. 2021Reinforcement Learning for Mixed Autonomy Intersectionscited by 16
  6. 2022An Introduction to Multi-Agent Reinforcement Learning and Review of its Application to Autonomous Mobilitycited by 16
  7. 2019A Fleet of Miniature Cars for Experiments in Cooperative Drivingcited by 10
  8. 2022Cooperative Behavior Planning for Automated Driving using Graph Neural Networkscited by 10
  9. 2022Potential Game-Based Decision-Making for Autonomous Drivingcited by 9
  10. 2019A Review on Energy, Environmental, and Sustainability Implications of Connected and Automated Vehiclescited by 7
  11. 2023A Survey of Generative AI for Intelligent Transportation Systems: Road Transportation Perspectivecited by 6
  12. 2022An Enhanced Graph Representation for Machine Learning Based Automatic Intersection Managementcited by 4

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Cited by year

Citing papers per year: 2025: 1.

1 paper.

  1. 2025A Fairness-Oriented Multi-Objective Reinforcement Learning approach for Autonomous Intersection Managementcited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2024A Systematic Study of Multi-Agent Deep Reinforcement Learning for Safe and Robust Autonomous Highway Ramp Entry
  2. 2026Compact Latent Coordination for Autonomous Vehicles at Unsignalized Intersections
  3. 2024Cooperative Decision-Making for CAVs at Unsignalized Intersections: A MARL Approach with Attention and Hierarchical Game Priors
  4. 2024Autonomous Driving at Unsignalized Intersections: A Review of Decision-Making Challenges and Reinforcement Learning-Based Solutions
  5. 2025Resolve Highway Conflict in Multi-Autonomous Vehicle Controls with Local State Attention
  6. 2026A Distributionally Robust Multi-agent Reinforcement Learning Framework for Intelligent Intersection Control ↗
  7. 2024Multi-Agent Reinforcement Learning for Autonomous Driving: A Survey
  8. 2022Adaptive Decision Making at the Intersection for Autonomous Vehicles Based on Skill Discovery