mlsanityData to 7 Oct 2026

Waymax: An Accelerated, Data-Driven Simulator for Large-Scale Autonomous Driving Research

arXiv 2310.08710 ↗First posted 12 Oct 2023cs.RO cs.LGcited by 158

On the map: World models → World models for autonomous driving

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Abstract (arXiv)

Simulation is an essential tool to develop and benchmark autonomous vehicle planning software in a safe and cost-effective manner. However, realistic simulation requires accurate modeling of nuanced and complex multi-agent interactive behaviors. To address these challenges, we introduce Waymax, a new data-driven simulator for autonomous driving in multi-agent scenes, designed for large-scale simulation and testing. Waymax uses publicly-released, real-world driving data (e.g., the Waymo Open Motion Dataset) to initialize or play back a diverse set of multi-agent simulated scenarios. It runs entirely on hardware accelerators such as TPUs/GPUs and supports in-graph simulation for training, making it suitable for modern large-scale, distributed machine learning workflows. To support online training and evaluation, Waymax includes several learned and hard-coded behavior models that allow for realistic interaction within simulation. To supplement Waymax, we benchmark a suite of popular imitation and reinforcement learning algorithms with ablation studies on different design decisions, where we highlight the effectiveness of routes as guidance for planning agents and the ability of RL to overfit against simulated agents.

Key facts. Cited by 158 papers in the map (data through 7 Oct 2026). Placed in World models for autonomous driving, one of 11 directions in World models. Builds on 41 of its 55 references that are in the map. First posted on arXiv 12 Oct 2023.

Builds on

41 of 55 references.

Closest ancestors · 5

Same direction, newest first

  1. 2022Wayformer: Motion Forecasting via Simple & Efficient Attention Networks12 Jul
  2. 2021MetaDrive: Composing Diverse Driving Scenarios for Generalizable Reinforcement Learning26 Sep
  3. 2021NuPlan: A closed-loop ML-based planning benchmark for autonomous vehicles22 Jun
  4. 2021Scene Transformer: A unified architecture for predicting multiple agent trajectories15 Jun
  5. 2017CARLA: An Open Urban Driving Simulator10 Nov

Other references · 36

  1. 2017Domain Randomization for Transferring Deep Neural Networks from Simulation to the Real Worldcited by 1,401
  2. 2015Prioritized Experience Replaycited by 1,070
  3. 2016End to End Learning for Self-Driving Carscited by 1,000
  4. 2022Block-NeRF: Scalable Large Scene Neural View Synthesiscited by 720
  5. 2021Large Scale Interactive Motion Forecasting for Autonomous Driving : The Waymo Open Motion Datasetcited by 532
  6. 2017End-to-end Driving via Conditional Imitation Learningcited by 479
  7. 2019MultiPath: Multiple Probabilistic Anchor Trajectory Hypotheses for Behavior Predictioncited by 417
  8. 2018ChauffeurNet: Learning to Drive by Imitating the Best and Synthesizing the Worstcited by 391
  9. 2020Learning Lane Graph Representations for Motion Forecastingcited by 380
  10. 2021Brax -- A Differentiable Physics Engine for Large Scale Rigid Body Simulationcited by 375
  11. 2019Learning by Cheatingcited by 361
  12. 2021DenseTNT: End-to-end Trajectory Prediction from Dense Goal Setscited by 292
24 more
  1. 2019Causal Confusion in Imitation Learningcited by 286
  2. 2018Learning to Drive in a Daycited by 266
  3. 2019PRECOG: PREdiction Conditioned On Goals in Visual Multi-Agent Settingscited by 178
  4. 2019Multiple Futures Predictioncited by 178
  5. 2020Acme: A Research Framework for Distributed Reinforcement Learningcited by 146
  6. 2022Imitation Is Not Enough: Robustifying Imitation with Reinforcement Learning for Challenging Driving Scenarioscited by 124
  7. 2020SMARTS: Scalable Multi-Agent Reinforcement Learning Training School for Autonomous Drivingcited by 121
  8. 2021VISTA 2.0: An Open, Data-driven Simulator for Multimodal Sensing and Policy Learning for Autonomous Vehiclescited by 81
  9. 2022BITS: Bi-level Imitation for Traffic Simulationcited by 80
  10. 2021SafetyNet: Safe planning for real-world self-driving vehicles using machine-learned policiescited by 68
  11. 2022Symphony: Learning Realistic and Diverse Agents for Autonomous Driving Simulationcited by 61
  12. 2022Nocturne: a scalable driving benchmark for bringing multi-agent learning one step closer to the real worldcited by 56
  13. 2019Multi-Agent Connected Autonomous Driving using Deep Reinforcement Learningcited by 53
  14. 2019Simulation-based reinforcement learning for real-world autonomous drivingcited by 51
  15. 2018A Reinforcement Learning Based Approach for Automated Lane Change Maneuverscited by 44
  16. 2022Hierarchical Model-Based Imitation Learning for Planning in Autonomous Drivingcited by 43
  17. 2019SUMMIT: A Simulator for Urban Driving in Massive Mixed Trafficcited by 39
  18. 2021Imagining The Road Ahead: Multi-Agent Trajectory Prediction via Differentiable Simulationcited by 32
  19. 2017Sim4CV: A Photo-Realistic Simulator for Computer Vision Applicationscited by 31
  20. 2022InterSim: Interactive Traffic Simulation via Explicit Relation Modelingcited by 27
  21. 2017Beyond Grand Theft Auto V for Training, Testing and Enhancing Deep Learning in Self Driving Carscited by 26
  22. 2021DriverGym: Democratising Reinforcement Learning for Autonomous Drivingcited by 23
  23. 2023Deep RL at Scale: Sorting Waste in Office Buildings with a Fleet of Mobile Manipulatorscited by 21
  24. 2020MADRaS : Multi Agent Driving Simulatorcited by 15

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 7; 2024: 43; 2025: 59; 2026: 49.

158 papers.

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By area:

  1. 2024NAVSIM: Data-Driven Non-Reactive Autonomous Vehicle Simulation and Benchmarkingcited by 343
  2. 2023A Survey on Multimodal Large Language Models for Autonomous Drivingcited by 288
  3. 2024Bench2Drive: Towards Multi-Ability Benchmarking of Closed-Loop End-To-End Autonomous Drivingcited by 250
  4. 2024Understanding World or Predicting Future? A Comprehensive Survey of World Modelscited by 161
  5. 2025End-to-End Driving with Online Trajectory Evaluation via BEV World Modelcited by 145
  6. 2025Pseudo-Simulation for Autonomous Drivingcited by 141
  7. 2024DriveArena: A Closed-loop Generative Simulation Platform for Autonomous Drivingcited by 98
  8. 2024DrivingGPT: Unifying Driving World Modeling and Planning with Multi-modal Autoregressive Transformerscited by 96
  9. 2025Hydra-MDP++: Advancing End-to-End Driving via Expert-Guided Hydra-Distillationcited by 93
  10. 2025Robust Autonomy Emerges from Self-Playcited by 64
  11. 2024NeuroNCAP: Photorealistic Closed-loop Safety Testing for Autonomous Drivingcited by 61
  12. 2025A Survey of World Models for Autonomous Drivingcited by 60
38 more
  1. 2024LidarDM: Generative LiDAR Simulation in a Generated Worldcited by 53
  2. 2023RealGen: Retrieval Augmented Generation for Controllable Traffic Scenarioscited by 46
  3. 2024GPUDrive: Data-driven, multi-agent driving simulation at 1 million FPScited by 43
  4. 2023Open-TI: Open Traffic Intelligence with Augmented Language Modelcited by 38
  5. 2024PlanAgent: A Multi-modal Large Language Agent for Closed-loop Vehicle Motion Planningcited by 38
  6. 2025Foundation Models in Autonomous Driving: A Survey on Scenario Generation and Scenario Analysiscited by 37
  7. 2025A Survey of Sim-to-Real Methods in RL: Progress, Prospects and Challenges with Foundation Modelscited by 36
  8. 2025VaViM and VaVAM: Autonomous Driving through Video Generative Modelingcited by 34
  9. 2025CaRL: Learning Scalable Planning Policies with Simple Rewardscited by 34
  10. 2024Multi-Agent Reinforcement Learning for Autonomous Driving: A Surveycited by 30
  11. 2024Hidden Biases of End-to-End Driving Datasetscited by 30
  12. 2023Towards Knowledge-driven Autonomous Drivingcited by 29
  13. 2025The Role of World Models in Shaping Autonomous Driving: A Comprehensive Surveycited by 29
  14. 2024SLEDGE: Synthesizing Driving Environments with Generative Models and Rule-Based Trafficcited by 27
  15. 2024Improving Agent Behaviors with RL Fine-tuning for Autonomous Drivingcited by 27
  16. 2025Scenario Dreamer: Vectorized Latent Diffusion for Generating Driving Simulation Environmentscited by 27
  17. 2023Choose Your Simulator Wisely: A Review on Open-source Simulators for Autonomous Drivingcited by 26
  18. 2024Text2LiDAR: Text-guided LiDAR Point Cloud Generation via Equirectangular Transformercited by 26
  19. 2024SMART: Scalable Multi-agent Real-time Motion Generation via Next-token Predictioncited by 25
  20. 2025LEAD: Minimizing Learner-Expert Asymmetry in End-to-End Drivingcited by 22
  21. 2025Building reliable sim driving agents by scaling self-playcited by 20
  22. 2025SceneDiffuser++: City-Scale Traffic Simulation via a Generative World Modelcited by 20
  23. 2024Human-compatible driving partners through data-regularized self-play reinforcement learningcited by 17
  24. 2025Towards Autonomous Micromobility through Scalable Urban Simulationcited by 16
  25. 2025Zero-Human Demonstration End-to-end Autonomous Driving with Trajectory Scorercited by 16
  26. 2024Urban Scene Diffusion through Semantic Occupancy Mapcited by 14
  27. 2024Bench2Drive-R: Turning Real World Data into Reactive Closed-Loop Autonomous Driving Benchmark by Generative Modelcited by 14
  28. 2025RefAV: Towards Planning-Centric Scenario Miningcited by 13
  29. 2025Virtual Community: An Open World for Humans, Robots, and Societycited by 13
  30. 2024CIMRL: Combining IMitation and Reinforcement Learning for Safe Autonomous Drivingcited by 12
  31. 2024CaDRE: Controllable and Diverse Generation of Safety-Critical Driving Scenarios using Real-World Trajectoriescited by 11
  32. 2024Multi-Agent Imitation Learning: Value is Easy, Regret is Hardcited by 11
  33. 2024Learning to Drive via Asymmetric Self-Playcited by 11
  34. 2025RealEngine: Simulating Autonomous Driving in Realistic Contextcited by 10
  35. 2025SceneCrafter: Controllable Multi-View Driving Scene Editingcited by 9
  36. 2024MoST: Multi-modality Scene Tokenization for Motion Predictioncited by 8
  37. 2024ReGentS: Real-World Safety-Critical Driving Scenario Generation Made Stablecited by 8
  38. 2024Learning Multiple Probabilistic Decisions from Latent World Model in Autonomous Drivingcited by 8

50 most cited of 158 All 158 (JSON)

Similar, not cited

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  1. 2023TrafficBots: Towards World Models for Autonomous Driving Simulation and Motion Prediction
  2. 2021Learning Interactive Driving Policies via Data-driven Simulation
  3. 2026TerraZero: Procedural Driving Simulation for Zero-Demonstration Self-Play at Scale
  4. 2025Advancing Multi-agent Traffic Simulation via R1-Style Reinforcement Fine-Tuning
  5. 2024Investigating Driving Interactions: A Robust Multi-Agent Simulation Framework for Autonomous Vehicles
  6. 2024EasyChauffeur: A Baseline Advancing Simplicity and Efficiency on Waymax
  7. 2023GameFormer: Game-theoretic Modeling and Learning of Transformer-based Interactive Prediction and Planning for Autonomous Driving
  8. 2024DriveGPT: Scaling Autoregressive Behavior Models for Driving