mlsanityData to 7 Oct 2026

LibSignal: An Open Library for Traffic Signal Control

arXiv 2211.10649 ↗First posted 19 Nov 2022cs.LGcited by 16

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Abstract (arXiv)

This paper introduces a library for cross-simulator comparison of reinforcement learning models in traffic signal control tasks. This library is developed to implement recent state-of-the-art reinforcement learning models with extensible interfaces and unified cross-simulator evaluation metrics. It supports commonly-used simulators in traffic signal control tasks, including Simulation of Urban MObility(SUMO) and CityFlow, and multiple benchmark datasets for fair comparisons. We conducted experiments to validate our implementation of the models and to calibrate the simulators so that the experiments from one simulator could be referential to the other. Based on the validated models and calibrated environments, this paper compares and reports the performance of current state-of-the-art RL algorithms across different datasets and simulators. This is the first time that these methods have been compared fairly under the same datasets with different simulators.

Key facts. Cited by 16 papers in the map (data through 7 Oct 2026). Builds on 15 of its 35 references that are in the map. First posted on arXiv 19 Nov 2022.

Builds on

15 of 35 references.

References · 15

  1. 2016OpenAI Gymcited by 1,684
  2. 2017Sim-to-Real Transfer of Robotic Control with Dynamics Randomizationcited by 616
  3. 2020Sim-to-Real Transfer in Deep Reinforcement Learning for Robotics: a Surveycited by 388
  4. 2020PettingZoo: Gym for Multi-Agent Reinforcement Learningcited by 209
  5. 2019Multi-Agent Deep Reinforcement Learning for Large-scale Traffic Signal Controlcited by 159
  6. 2019CoLight: Learning Network-level Cooperation for Traffic Signal Controlcited by 133
  7. 2019CityFlow: A Multi-Agent Reinforcement Learning Environment for Large Scale City Traffic Scenariocited by 114
  8. 2019Learning Phase Competition for Traffic Signal Controlcited by 84
  9. 2019A Survey on Traffic Signal Control Methodscited by 78
  10. 2020AttendLight: Universal Attention-Based Reinforcement Learning Model for Traffic Signal Controlcited by 60
  11. 2019Diagnosing Reinforcement Learning for Traffic Signal Controlcited by 33
  12. 2020IG-RL: Inductive Graph Reinforcement Learning for Massive-Scale Traffic Signal Controlcited by 20
3 more
  1. 2020GeneraLight: Improving Environment Generalization of Traffic Signal Control via Meta Reinforcement Learningcited by 17
  2. 2021DynSTGAT: Dynamic Spatial-Temporal Graph Attention Network for Traffic Signal Controlcited by 11
  3. 2021A Deep Reinforcement Learning Approach for Fair Traffic Signal Controlcited by 7

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2022: 1; 2023: 2; 2024: 5; 2025: 5; 2026: 3.

16 papers.

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  1. 2023Open-TI: Open Traffic Intelligence with Augmented Language Modelcited by 38
  2. 2024eTraM: Event-based Traffic Monitoring Datasetcited by 24
  3. 2024CoMAL: Collaborative Multi-Agent Large Language Models for Mixed-Autonomy Trafficcited by 22
  4. 2022SafeLight: A Reinforcement Learning Method toward Collision-free Traffic Signal Controlcited by 15
  5. 2025Large Language Models and Their Applications in Roadway Safety and Mobility Enhancement: A Comprehensive Reviewcited by 8
  6. 2024Towards Multi-agent Reinforcement Learning based Traffic Signal Control through Spatio-temporal Hypergraphscited by 5
  7. 2024SynTraC: A Synthetic Dataset for Traffic Signal Control from Traffic Monitoring Camerascited by 4
  8. 2023Uncertainty-aware Grounded Action Transformation towards Sim-to-Real Transfer for Traffic Signal Controlcited by 3
  9. 2025VLMLight: Safety-Critical Traffic Signal Control via Vision-Language Meta-Control and Dual-Branch Reasoning Architecturecited by 3
  10. 2025TranSimHub:A Unified Air-Ground Simulation Platform for Multi-Modal Perception and Decision-Makingcited by 3
  11. 2024PyTSC: A Unified Platform for Multi-Agent Reinforcement Learning in Traffic Signal Controlcited by 1
  12. 2025Joint-Local Grounded Action Transformation for Sim-to-Real Transfer in Multi-Agent Traffic Controlcited by 0
4 more
  1. 2025CFLight: Enhancing Safety with Traffic Signal Control through Counterfactual Learningcited by 0
  2. 2026HONEST-CAV: Hierarchical Optimization of Network Signals and Trajectories for Connected and Automated Vehicles with Multi-Agent Reinforcement Learningcited by 0
  3. 2026OracleTSC: Oracle-Informed Reward Hurdle and Uncertainty Regularization for Traffic Signal Controlcited by 0
  4. 2026Preference-Conditioned Multi-Objective Reinforcement Learning for Runtime-Tunable Transit Signal Prioritycited by 0