World models for autonomous driving
Key facts. World models for autonomous driving: 320 papers on arXiv since 2013 (data through 7 Oct 2026). 139 of its 320 mapped papers (43%) cite “GAIA-1: A Generative World Model for Autonomous Driving” (2023, arXiv 2309.17080). 123 of its 320 mapped papers (38%) cite “Driving into the Future: Multiview Visual Forecasting and Planning with World Model for Autonomous Driving” (2023, arXiv 2311.17918). 19 new papers 17 Sep–7 Oct.
What’s new
17 Sep – 7 Oct 2026
19 new papers, 17 Sep – 7 Oct; 1 this week.
- This week · 1
- GeoWM: Efficient Direct World Modeling in Explicit Geometry also fits: Video-generation world models and simulators
- Earlier · 18
- ReWAM: Reciprocal World Action Models for Interactive Autonomous Driving also fits: World models for navigation
- V2X-WAM: A Cooperative World Action Model for End-to-End Autonomous Driving
- RoXDrive: Closed-Loop Reinforcement Learning for End-to-End Autonomous Driving via Action-Faithful Rollouts
- MomWorld: Momentum-Aware Latent World Model for Long-Horizon Autonomous Driving
- PhysWAM: Physically Consistent World Action Model for Autonomous Driving
- World4Scorer: Outcome-Grounded World Modeling for Autonomous Driving
- CoDrive: Cross-Vehicle World-Consistent Video Generation with Precise Trajectory Control for Cooperative Driving
- AD-E2E-JEPA: A Joint-Embedding Predictive Architecture For End-to-End Autonomous Driving
- ReDrive: Shaping Representations with World Modeling for End-to-End Driving
All 19
- VehDyn: A Driving World Model Benchmark for Vehicle Dynamics
- WALT: Learning World-Model-Aligned Latent Trajectories for Autonomous Driving
- HelloWorld: Towards Practical Applications of Generative Driving World Models
- SlackDrive: Reclaiming Runtime Slack for Adaptive Driving Inference
- ForeDrive: Foresight-Guided End-to-End Autonomous Driving with a Planning-Relevant Latent World Model
- Relationally Grounded Latent World Models for Autonomous Driving
- DriveReferee: Geometric Safety Verdicts Need Not Be Learned for Driving World-Action Models
- ZYT-World: A Real-Time Controllable World Model for Closed-Loop Autonomous-Driving Simulation
- MM-Future: Multi-Mode Joint World-Action Modeling for Autonomous Driving
Foundations
Most cited by papers here
- GAIA-1: A Generative World Model for Autonomous Driving2023cited by 139 here
- Driving into the Future: Multiview Visual Forecasting and Planning with World Model for Autonomous Driving2023cited by 123 here
- Vista: A Generalizable Driving World Model with High Fidelity and Versatile Controllability2024cited by 115 here
- CARLA: An Open Urban Driving Simulator2017cited by 95 here
- OccWorld: Learning a 3D Occupancy World Model for Autonomous Driving2023cited by 94 here
Lineage
The papers this direction builds on, oldest first.
Each paper on the line cites the one before.
- 2018World Modelscited by 57 here
- 2019Dream to Control: Learning Behaviors by Latent Imaginationcited by 53 here
- 2020Mastering Atari with Discrete World Modelscited by 43 here
- 2023Mastering Diverse Domains through World Modelscited by 45 here
- 2023DriveDreamer: Towards Real-world-driven World Models for Autonomous Drivingcited by 84 here
- 2023GAIA-1: A Generative World Model for Autonomous Drivingcited by 139 here
- 2023Driving into the Future: Multiview Visual Forecasting and Planning with World Model for Autonomous Drivingcited by 123 here
- 2024DriveDreamer-2: LLM-Enhanced World Models for Diverse Driving Video Generationcited by 65 here
- 2024Vista: A Generalizable Driving World Model with High Fidelity and Versatile Controllabilitycited by 115 here
- 2025Epona: Autoregressive Diffusion World Model for Autonomous Drivingcited by 57 here
14 more it builds on, not in this chain
- 2017CARLA: An Open Urban Driving Simulatorcited by 95 here
- 2020Denoising Diffusion Probabilistic Modelscited by 51 here
- 2021NuPlan: A closed-loop ML-based planning benchmark for autonomous vehiclescited by 72 here
- 2022BEVFormer: Learning Bird's-Eye-View Representation from Multi-Camera Images via Spatiotemporal Transformerscited by 51 here
- 2022Scalable Diffusion Models with Transformerscited by 52 here
- 2023ADriver-I: A General World Model for Autonomous Drivingcited by 43 here
- 2023Stable Video Diffusion: Scaling Latent Video Diffusion Models to Large Datasetscited by 50 here
- 2023OccWorld: Learning a 3D Occupancy World Model for Autonomous Drivingcited by 94 here
- 2024GenAD: Generative End-to-End Autonomous Drivingcited by 48 here
- 2024GenAD: Generalized Predictive Model for Autonomous Drivingcited by 45 here
- 2024DriveWorld: 4D Pre-trained Scene Understanding via World Models for Autonomous Drivingcited by 47 here
- 2024Enhancing End-to-End Autonomous Driving with Latent World Modelcited by 72 here
- 2025End-to-End Driving with Online Trajectory Evaluation via BEV World Modelcited by 53 here
- 2025World4Drive: End-to-End Autonomous Driving via Intention-aware Physical Latent World Modelcited by 51 here
The 24 most cited of 394.
Browse
30 of 320, ranked 6–35
- 6DriveDreamer: Towards Real-world-driven World Models for Autonomous Driving202384
- 7Enhancing End-to-End Autonomous Driving with Latent World Model202472
- 8NuPlan: A closed-loop ML-based planning benchmark for autonomous vehicles202172
- 9DriveDreamer-2: LLM-Enhanced World Models for Diverse Driving Video Generation202465
- 10Epona: Autoregressive Diffusion World Model for Autonomous Driving202557
- 11End-to-End Driving with Online Trajectory Evaluation via BEV World Model202553
- 12World4Drive: End-to-End Autonomous Driving via Intention-aware Physical Latent World Model202551
- 13BEVFormer: Learning Bird's-Eye-View Representation from Multi-Camera Images via Spatiotemporal Transformers202251
- 14GenAD: Generative End-to-End Autonomous Driving202448
- 15DriveWorld: 4D Pre-trained Scene Understanding via World Models for Autonomous Driving202447
All 30
- 16GenAD: Generalized Predictive Model for Autonomous Driving202445
- 17DriveVLA-W0: World Models Amplify Data Scaling Law in Autonomous Driving202543
- 18DrivingGPT: Unifying Driving World Modeling and Planning with Multi-modal Autoregressive Transformers202443
- 19ADriver-I: A General World Model for Autonomous Driving202343
- 20Occ3D: A Large-Scale 3D Occupancy Prediction Benchmark for Autonomous Driving202338
- 21GAIA-2: A Controllable Multi-View Generative World Model for Autonomous Driving202536
- 22Copilot4D: Learning Unsupervised World Models for Autonomous Driving via Discrete Diffusion202333
- 23Visual Point Cloud Forecasting enables Scalable Autonomous Driving202333
- 24Point Cloud Forecasting as a Proxy for 4D Occupancy Forecasting202332
- 25Driving in the Occupancy World: Vision-Centric 4D Occupancy Forecasting and Planning via World Models for Autonomous Driving202431
- 26DriveDreamer4D: World Models Are Effective Data Machines for 4D Driving Scene Representation202431
- 27World Models for Autonomous Driving: An Initial Survey202429
- 28DOME: Taming Diffusion Model into High-Fidelity Controllable Occupancy World Model202427
- 29OccLLaMA: An Occupancy-Language-Action Generative World Model for Autonomous Driving202426
- 30ReSim: Reliable World Simulation for Autonomous Driving202525
- 31Differentiable Raycasting for Self-supervised Occupancy Forecasting202225
- 32Doe-1: Closed-Loop Autonomous Driving with Large World Model202424
- 33DrivingWorld: Constructing World Model for Autonomous Driving via Video GPT202424
- 34Enhance Sample Efficiency and Robustness of End-to-end Urban Autonomous Driving via Semantic Masked World Model202224
- 35Street Gaussians: Modeling Dynamic Urban Scenes with Gaussian Splatting202423