mlsanityData to 7 Oct 2026

Reinforcement Learning for Mixed Autonomy Intersections

arXiv 2111.04686 ↗First posted 8 Nov 2021cs.AI cs.LG cs.MAcited by 14

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Abstract (arXiv)

We propose a model-free reinforcement learning method for controlling mixed autonomy traffic in simulated traffic networks with through-traffic-only two-way and four-way intersections. Our method utilizes multi-agent policy decomposition which allows decentralized control based on local observations for an arbitrary number of controlled vehicles. We demonstrate that, even without reward shaping, reinforcement learning learns to coordinate the vehicles to exhibit traffic signal-like behaviors, achieving near-optimal throughput with 33-50% controlled vehicles. With the help of multi-task learning and transfer learning, we show that this behavior generalizes across inflow rates and size of the traffic network. Our code, models, and videos of results are available at https://github.com/ZhongxiaYan/mixed_autonomy_intersections.

Key facts. Cited by 14 papers in the map (data through 7 Oct 2026). Builds on 4 of its 22 references that are in the map. First posted on arXiv 8 Nov 2021.

Builds on

4 of 22 references.

References · 4

  1. 2017Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environmentscited by 1,519
  2. 2015Policy Distillationcited by 414
  3. 2019CoLight: Learning Network-level Cooperation for Traffic Signal Controlcited by 133
  4. 2016Polling-systems-based Autonomous Vehicle Coordination in Traffic Intersections with No Traffic Signalscited by 4

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Cited by year

Citing papers per year: 2022: 2; 2023: 5; 2024: 4; 2025: 3.

14 papers.

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  1. 2023Can ChatGPT Enable ITS? The Case of Mixed Traffic Control via Reinforcement Learningcited by 18
  2. 2022Unified Automatic Control of Vehicular Systems with Reinforcement Learningcited by 13
  3. 2022Learning Eco-Driving Strategies at Signalized Intersectionscited by 9
  4. 2023Learning to Control and Coordinate Mixed Traffic Through Robot Vehicles at Complex and Unsignalized Intersectionscited by 9
  5. 2023Mixed Traffic Control and Coordination from Pixelscited by 8
  6. 2023Temporal Transfer Learning for Traffic Optimization with Coarse-grained Advisory Autonomycited by 6
  7. 2023PeRP: Personalized Residual Policies For Congestion Mitigation Through Co-operative Advisory Systemscited by 4
  8. 2025A Survey of Reinforcement Learning-Based Motion Planning for Autonomous Driving: Lessons Learned from a Driving Task Perspectivecited by 2
  9. 2025Large-Scale Mixed-Traffic and Intersection Control using Multi-agent Reinforcement Learningcited by 2
  10. 2024Cooperative Advisory Residual Policies for Congestion Mitigationcited by 1
  11. 2024A Distributed Approach to Autonomous Intersection Management via Multi-Agent Reinforcement Learningcited by 0
  12. 2024Lessons in Cooperation: A Qualitative Analysis of Driver Sentiments towards Real-Time Advisory Systems from a Driving Simulator User Studycited by 0
2 more
  1. 2024Neighbor-Aware Reinforcement Learning for Mixed Traffic Optimization in Large-scale Networkscited by 0
  2. 2025Multi-Objective Reinforcement Learning for Large-Scale Mixed Traffic Controlcited by 0