mlsanityData to 7 Oct 2026

Nocturne: a scalable driving benchmark for bringing multi-agent learning one step closer to the real world

arXiv 2206.09889 ↗First posted 20 Jun 2022cs.MA cs.AI cs.LGcited by 56

Not on the map. Why?

Cited by 31 in End-to-end autonomous driving, but placed by its own abstract, which didn’t fit.

Abstract (arXiv)

We introduce Nocturne, a new 2D driving simulator for investigating multi-agent coordination under partial observability. The focus of Nocturne is to enable research into inference and theory of mind in real-world multi-agent settings without the computational overhead of computer vision and feature extraction from images. Agents in this simulator only observe an obstructed view of the scene, mimicking human visual sensing constraints. Unlike existing benchmarks that are bottlenecked by rendering human-like observations directly using a camera input, Nocturne uses efficient intersection methods to compute a vectorized set of visible features in a C++ back-end, allowing the simulator to run at over 2000 steps-per-second. Using open-source trajectory and map data, we construct a simulator to load and replay arbitrary trajectories and scenes from real-world driving data. Using this environment, we benchmark reinforcement-learning and imitation-learning agents and demonstrate that the agents are quite far from human-level coordination ability and deviate significantly from the expert trajectories.

Key facts. Cited by 56 papers in the map (data through 7 Oct 2026). Builds on 26 of its 41 references that are in the map. First posted on arXiv 20 Jun 2022.

Builds on

26 of 41 references.

References · 26

  1. 2019PyTorch: An Imperative Style, High-Performance Deep Learning Librarycited by 20,160
  2. 2019nuScenes: A multimodal dataset for autonomous drivingcited by 4,485
  3. 2014Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translationcited by 4,016
  4. 2021The Surprising Effectiveness of PPO in Cooperative, Multi-Agent Gamescited by 903
  5. 2019The StarCraft Multi-Agent Challengecited by 589
  6. 2021Large Scale Interactive Motion Forecasting for Autonomous Driving : The Waymo Open Motion Datasetcited by 532
  7. 2020VectorNet: Encoding HD Maps and Agent Dynamics from Vectorized Representationcited by 528
  8. 2021MetaDrive: Composing Diverse Driving Scenarios for Generalizable Reinforcement Learningcited by 281
  9. 2019Google Research Football: A Novel Reinforcement Learning Environmentcited by 257
  10. 2020One Thousand and One Hours: Self-driving Motion Prediction Datasetcited by 239
  11. 2019INTERACTION Dataset: An INTERnational, Adversarial and Cooperative moTION Dataset in Interactive Driving Scenarios with Semantic Mapscited by 231
  12. 2019The Hanabi Challenge: A New Frontier for AI Researchcited by 194
14 more
  1. 2020"Other-Play" for Zero-Shot Coordinationcited by 194
  2. 2021TrafficSim: Learning to Simulate Realistic Multi-Agent Behaviorscited by 192
  3. 2020SMARTS: Scalable Multi-Agent Reinforcement Learning Training School for Autonomous Drivingcited by 121
  4. 2021Scalable Evaluation of Multi-Agent Reinforcement Learning with Melting Potcited by 97
  5. 2020Sample Factory: Egocentric 3D Control from Pixels at 100000 FPS with Asynchronous Reinforcement Learningcited by 84
  6. 2021VISTA 2.0: An Open, Data-driven Simulator for Multimodal Sensing and Policy Learning for Autonomous Vehiclescited by 81
  7. 2022Symphony: Learning Realistic and Diverse Agents for Autonomous Driving Simulationcited by 61
  8. 2019Multi-Agent Connected Autonomous Driving using Deep Reinforcement Learningcited by 53
  9. 2019SUMMIT: A Simulator for Urban Driving in Massive Mixed Trafficcited by 39
  10. 2017Sim4CV: A Photo-Realistic Simulator for Computer Vision Applicationscited by 31
  11. 2021DriverGym: Democratising Reinforcement Learning for Autonomous Drivingcited by 23
  12. 2020BARK: Open Behavior Benchmarking in Multi-Agent Environmentscited by 21
  13. 2020MADRaS : Multi Agent Driving Simulatorcited by 15
  14. 2020Emergent Road Rules In Multi-Agent Driving Environmentscited by 8

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2022: 1; 2023: 8; 2024: 19; 2025: 16; 2026: 12.

56 papers.

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  1. 2023DriveMLM: Aligning Multi-Modal Large Language Models with Behavioral Planning States for Autonomous Drivingcited by 233
  2. 2023Waymax: An Accelerated, Data-Driven Simulator for Large-Scale Autonomous Driving Researchcited by 158
  3. 2025Pseudo-Simulation for Autonomous Drivingcited by 141
  4. 2022Imitation Is Not Enough: Robustifying Imitation with Reinforcement Learning for Challenging Driving Scenarioscited by 124
  5. 2023The Waymo Open Sim Agents Challengecited by 86
  6. 2025Robust Autonomy Emerges from Self-Playcited by 64
  7. 2024BehaviorGPT: Smart Agent Simulation for Autonomous Driving with Next-Patch Predictioncited by 49
  8. 2024SceneDiffuser: Efficient and Controllable Driving Simulation Initialization and Rolloutcited by 47
  9. 2024GPUDrive: Data-driven, multi-agent driving simulation at 1 million FPScited by 43
  10. 2025Foundation Models in Autonomous Driving: A Survey on Scenario Generation and Scenario Analysiscited by 37
  11. 2023Inverse Reinforcement Learning without Reinforcement Learningcited by 35
  12. 2024Hybrid Inverse Reinforcement Learningcited by 31
38 more
  1. 2024Multi-Agent Reinforcement Learning for Autonomous Driving: A Surveycited by 30
  2. 2024DriVLMe: Enhancing LLM-based Autonomous Driving Agents with Embodied and Social Experiencescited by 27
  3. 2024Improving Agent Behaviors with RL Fine-tuning for Autonomous Drivingcited by 27
  4. 2025Scenario Dreamer: Vectorized Latent Diffusion for Generating Driving Simulation Environmentscited by 27
  5. 2023Choose Your Simulator Wisely: A Review on Open-source Simulators for Autonomous Drivingcited by 26
  6. 2024CtRL-Sim: Reactive and Controllable Driving Agents with Offline Reinforcement Learningcited by 26
  7. 2023Learning Realistic Traffic Agents in Closed-loopcited by 24
  8. 2024POGEMA: A Benchmark Platform for Cooperative Multi-Agent Pathfindingcited by 20
  9. 2025Building reliable sim driving agents by scaling self-playcited by 20
  10. 2023A Model-Based Solution to the Offline Multi-Agent Reinforcement Learning Coordination Problemcited by 18
  11. 2024Human-compatible driving partners through data-regularized self-play reinforcement learningcited by 17
  12. 2024Multi-Agent Imitation Learning: Value is Easy, Regret is Hardcited by 11
  13. 2024Learning to Drive via Asymmetric Self-Playcited by 11
  14. 2024Non-Adversarial Inverse Reinforcement Learning via Successor Feature Matchingcited by 10
  15. 2025Multi-agent Coordination via Flow Matchingcited by 9
  16. 2023Prospective Role of Foundation Models in Advancing Autonomous Vehiclescited by 7
  17. 2024EvIL: Evolution Strategies for Generalisable Imitation Learningcited by 7
  18. 2025When Planners Meet Reality: How Learned, Reactive Traffic Agents Shift nuPlan Benchmarkscited by 7
  19. 2024TorchDriveEnv: A Reinforcement Learning Benchmark for Autonomous Driving with Reactive, Realistic, and Diverse Non-Playable Characterscited by 6
  20. 2024IntersectionZoo: Eco-driving for Benchmarking Multi-Agent Contextual Reinforcement Learningcited by 6
  21. 2026Learning to Drive in New Cities Without Human Demonstrationscited by 6
  22. 2026Human-like autonomy emerges from self-play and a pinch of human datacited by 4
  23. 2026Scaling Self-Play for End-to-End Drivingcited by 4
  24. 2024Adversarial and Reactive Traffic Entities for Behavior-Realistic Driving Simulation: A Reviewcited by 3
  25. 2024IGDrivSim: A Benchmark for the Imitation Gap in Autonomous Drivingcited by 3
  26. 2025Getting SMARTER for Motion Planning in Autonomous Driving Systemscited by 3
  27. 2025V-Max: A Reinforcement Learning Framework for Autonomous Drivingcited by 3
  28. 2025SceneStreamer: Continuous Scenario Generation as Next Token Group Predictioncited by 2
  29. 2025CAMAR: Continuous Actions Multi-Agent Routingcited by 2
  30. 2024Agent-Agnostic Centralized Training for Decentralized Multi-Agent Cooperative Drivingcited by 1
  31. 2025Unlocking Efficient Vehicle Dynamics Modeling via Analytic World Modelscited by 1
  32. 2025Controllable risk scenario generation from human crash data for autonomous vehicle testingcited by 1
  33. 2026TerraZero: Procedural Driving Simulation for Zero-Demonstration Self-Play at Scalecited by 1
  34. 2026Scaling Curriculum Learning For Autonomous Drivingcited by 1
  35. 2025Sky-Drive: A Distributed Multi-Agent Simulation Platform for Human-AI Collaborative and Socially-Aware Future Transportationcited by 0
  36. 2025Training Environment for High Performance Reinforcement Learningcited by 0
  37. 2025TreeIRL: Safe Urban Driving with Tree Search and Inverse Reinforcement Learningcited by 0
  38. 2026OccSim: Multi-kilometer Simulation with Long-horizon Occupancy World Modelscited by 0

50 most cited of 56 All 56 (JSON)