SceneDiffuser++: City-Scale Traffic Simulation via a Generative World Model
Shuhan Tan, John Lambert, Hong Jeon, Sakshum Kulshrestha, Yijing Bai, Jing Luo, Dragomir Anguelov, Mingxing Tan, Chiyu Max Jiang
Abstract
Simulation Route (a) Initial Scene Generation (b) Long Simulation Rollout (c) Final Destination Figure 1. Overview. SceneDiffuser++ is a single unified, end-to-end trained generative world model that enables CitySim: city-scale traffic simulation that takes in a large map region, start and end points, and simulates everything in between, from initial scene generation, agent behavior prediction, occlusion reasoning, dynamic agent generation (spawning and removal) to environment simulation (traffic lights).
Ask about this paper
Your agent reads all of it.
Lune indexed this paper to the last equation, along with the top-tier papers that cite it. Ask a question and the answer quotes them.
Your agent calls
Luneget_paper_fulltext
Free to start. No credit card required.
Terminal
Install the CLIlune papers fulltext 09445647-5b88-4a09-87b3-ea78dd7bde11Cited by top-tier papers3
- SceneStreamer: Continuous Scenario Generation as Next Token Group PredictionZhenghao Peng, Yuxin Liu, Bolei ZhouICLR 2026 · 5 citations
- Long-Term Traffic Simulation with Interleaved Autoregressive Motion and Scenario GenerationXiuyu Yang, Shuhan Tan, Philipp KrähenbühlICCV 2025 · 1 citation
- VectorWorld: Efficient Streaming World Model via Diffusion Flow on Vector GraphsChaokang Jiang, Desen Zhou, Jiuming Liu, Li SunICML 2026
Builds on17
- Mastering Atari with Discrete World ModelsDanijar Hafner, Timothy P. Lillicrap, Mohammad Norouzi, Jimmy BaICLR 2021 · 1,170 citations
- Large Scale Interactive Motion Forecasting for Autonomous Driving : The Waymo Open Motion DatasetScott Ettinger, Shuyang Cheng, Benjamin Caine, Chenxi Liu et al.ICCV 2021 · 817 citations
- Block-NeRF: Scalable Large Scene Neural View SynthesisMatthew Tancik, Vincent Casser, Xinchen Yan, Sabeek Pradhan et al.CVPR 2022 · 702 citations
- simple diffusion: End-to-end diffusion for high resolution imagesEmiel Hoogeboom, Jonathan Heek, Tim SalimansICML 2023 · 403 citations
- Scene Transformer: A unified architecture for predicting future trajectories of multiple agentsJiquan Ngiam, Vijay Vasudevan, Benjamin Caine, Zhengdong Zhang et al.ICLR 2022 · 194 citations
Related papers
- SceneDiffuser: Efficient and Controllable Driving Simulation Initialization and RolloutChiyu Max Jiang, Yijing Bai, Andre Cornman, Christopher Davis et al.NeurIPS 2024 · 76 citations
- Scenario Dreamer: Vectorized Latent Diffusion for Generating Driving Simulation EnvironmentsLuke Rowe, Roger Girgis, Anthony Gosselin, Liam Paull et al.CVPR 2025
- Diffusion-based Generation, Optimization, and Planning in 3D ScenesSiyuan Huang, Zan Wang, Puhao Li, Baoxiong Jia et al.CVPR 2023
- Scenario Diffusion: Controllable Driving Scenario Generation With DiffusionEthan Pronovost, Meghana Reddy Ganesina, Noureldin Hendy, Zeyu Wang et al.NeurIPS 2023 · 89 citations
- X-Scene: Large-Scale Driving Scene Generation with High Fidelity and Flexible ControllabilityYu Yang, Alan Liang, Jianbiao Mei, Yukai Ma et al.NeurIPS 2025 · 22 citations
