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We introduce Scenario Dreamer, a fully data-driven generative simulator for autonomous vehicle planning that generates both the initial traffic scene - comprising a lane graph and agent bounding boxes - and closed-loop agent behaviours.
Congested traffic states in empirical observations and microscopic simulations
Martin Treiber, Ansgar Hennecke, and Dirk Helbing · 2000
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General lane-changing model mobil for car-following models
Arne Kesting, Martin Treiber, and Dirk Helbing · 2007
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Auto-encoding variational bayes
Diederik P. Kingma and Max Welling · 2014
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CARLA: an open urban driving simulator
Alexey Dosovitskiy, Germán Ros, Felipe Codevilla, Antonio M. López, and Vladlen Koltun · 2017
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beta-VAE: Learning basic visual concepts with a constrained variational framework
Irina Higgins, Loic Matthey, Arka Pal, Christopher Burgess, Xavier Glorot, Matthew Botvinick, Shakir Mohamed, and Alexander Lerchner · 2017
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Proximal policy optimization algorithms
John Schulman, Filip Wolski, Prafulla Dhariwal, Alec Radford, and Oleg Klimov · 2017
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N. Gomez, Lukasz Kaiser, and Illia Polosukhin · 2017
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An environment for autonomous driving decision-making
Edouard Leurent · 2018
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Neural turtle graphics for modeling city road layouts
Hang Chu, Daiqing Li, David Acuna, Amlan Kar, Maria Shugrina, Xinkai Wei, Ming-Yu Liu, Antonio Torralba, and Sanja Fidler · 2019
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SUMMIT: A simulator for urban driving in massive mixed traffic
Panpan Cai, Yiyuan Lee, Yuanfu Luo, and David Hsu · 2020
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Vectornet: Encoding HD maps and agent dynamics from vectorized representation
Jiyang Gao, Chen Sun, Hang Zhao, Yi Shen, Dragomir Anguelov, Congcong Li, and Cordelia Schmid · 2020
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Denoising diffusion probabilistic models
Jonathan Ho, Ajay Jain, and Pieter Abbeel · 2020
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Learning lane graph representations for motion forecasting
Ming Liang, Bin Yang, Rui Hu, Yun Chen, Renjie Liao, Song Feng, and Raquel Urtasun · 2020
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Smarts: Scalable multi-agent reinforcement learning training school for autonomous driving, 2020
Ming Zhou, Jun Luo, Julian Villella, Yaodong Yang, David Rusu, Jiayu Miao, Weinan Zhang, Montgomery Alban, Iman Fadakar, Zheng Chen, Aurora Chongxi Huang, Ying Wen, Kimia Hassanzadeh, Daniel Graves, Dong Chen, Zhengbang Zhu, Nhat Nguyen, Mohamed Elsayed, Kun Shao, Sanjeevan Ahilan, Baokuan Zhang, Jiannan Wu, Zhengang Fu, Kasra Rezaee, Peyman Yadmellat, Mohsen Rohani, Nicolas Perez Nieves, Yihan Ni, Seyedershad Banijamali, Alexander Cowen Rivers, Zheng Tian, Daniel Palenicek, Haitham bou Ammar, Hongbo Zhang, Wulong Liu, Jianye Hao, and Jun Wang · 2020
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Simnet: Learning reactive self-driving simulations from real-world observations
Luca Bergamini, Yawei Ye, Oliver Scheel, Long Chen, Chih Hu, Luca Del Pero, Blazej Osinski, Hugo Grimmett, and Peter Ondruska · 2021
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Large scale interactive motion forecasting for autonomous driving : The waymo open motion dataset
Scott Ettinger, Shuyang Cheng, Benjamin Caine, Chenxi Liu, Hang Zhao, Sabeek Pradhan, Yuning Chai, Ben Sapp, Charles R. Qi, Yin Zhou, Zoey Yang, Aurelien Chouard, Pei Sun, Jiquan Ngiam, Vijay Vasudevan, Alexander McCauley, Jonathon Shlens, and Dragomir Anguelov · 2021
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Hdmapgen: A hierarchical graph generative model of high definition maps
Lu Mi, Hang Zhao, Charlie Nash, Xiaohan Jin, Jiyang Gao, Chen Sun, Cordelia Schmid, Nir Shavit, Yuning Chai, and Dragomir Anguelov · 2021
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Improved denoising diffusion probabilistic models
Alexander Quinn Nichol and Prafulla Dhariwal · 2021
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Neural scene graphs for dynamic scenes
Julian Ost, Fahim Mannan, Nils Thuerey, Julian Knodt, and Felix Heide · 2021
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Waymo simulated driving behavior in reconstructed fatal crashes within an autonomous vehicle operating domain
John M Scanlon, Kristofer D Kusano, Tom Daniel, Christopher Alderson, Alexander Ogle, and Trent Victor · 2021
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Trafficsim: Learning to simulate realistic multi-agent behaviors
Simon Suo, Sebastian Regalado, Sergio Casas, and Raquel Urtasun · 2021
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Scenegen: Learning to generate realistic traffic scenes
Shuhan Tan, Kelvin Wong, Shenlong Wang, Sivabalan Manivasagam, Mengye Ren, and Raquel Urtasun · 2021
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Latent variable sequential set transformers for joint multi-agent motion prediction
Roger Girgis, Florian Golemo, Felipe Codevilla, Martin Weiss, Jim Aldon D’Souza, Samira Ebrahimi Kahou, Felix Heide, and Christopher Joseph Pal · 2022
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Equivariant diffusion for molecule generation in 3d
Emiel Hoogeboom, Victor Garcia Satorras, Clément Vignac, and Max Welling · 2022
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Symphony: Learning realistic and diverse agents for autonomous driving simulation
Maximilian Igl, Daewoo Kim, Alex Kuefler, Paul Mougin, Punit Shah, Kyriacos Shiarlis, Dragomir Anguelov, Mark Palatucci, Brandyn White, and Shimon Whiteson · 2022
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Multi-game decision transformers
Kuang-Huei Lee, Ofir Nachum, Mengjiao Yang, Lisa Lee, Daniel Freeman, Sergio Guadarrama, Ian Fischer, Winnie Xu, Eric Jang, Henryk Michalewski, and Igor Mordatch · 2022
Cited alongside, same era.
Scene transformer: A unified architecture for predicting future trajectories of multiple agents
Jiquan Ngiam, Vijay Vasudevan, Benjamin Caine, Zhengdong Zhang, Hao-Tien Lewis Chiang, Jeffrey Ling, Rebecca Roelofs, Alex Bewley, Chenxi Liu, Ashish Venugopal, David J. Weiss, Ben Sapp, Zhifeng Chen, and Jonathon Shlens · 2022
Cited alongside, same era.
Hierarchical text-conditional image generation with CLIP latents
Aditya Ramesh, Prafulla Dhariwal, Alex Nichol, Casey Chu, and Mark Chen · 2022
Cited alongside, same era.
High-resolution image synthesis with latent diffusion models
Robin Rombach, Andreas Blattmann, Dominik Lorenz, Patrick Esser, and Björn Ommer · 2022
Cited alongside, same era.
Nocturne: a scalable driving benchmark for bringing multi-agent learning one step closer to the real world
Eugene Vinitsky, Nathan Lichtlé, Xiaomeng Yang, Brandon Amos, and Jakob Foerster · 2022
Cited alongside, same era.
Genie: Generative interactive environments
Jake Bruce, Michael D. Dennis, Ashley Edwards, Jack Parker-Holder, Yuge Shi, Edward Hughes, Matthew Lai, Aditi Mavalankar, Richie Steigerwald, Chris Apps, Yusuf Aytar, Sarah Bechtle, Feryal M. P. Behbahani, Stephanie C. Y. Chan, Nicolas Heess, Lucy Gonzalez, Simon Osindero, Sherjil Ozair, Scott E. Reed, Jingwei Zhang, Konrad Zolna, Jeff Clune, Nando de Freitas, Satinder Singh, and Tim Rocktäschel · 2024
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SLEDGE: synthesizing driving environments with generative models and rule-based traffic
Kashyap Chitta, Daniel Dauner, and Andreas Geiger · 2024
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Human-compatible driving agents through data-regularized self-play reinforcement learning
Daphne Cornelisse and Eugene Vinitsky · 2024
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Average annual miles per driver by age group
FHWA · 2024
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Vista: A generalizable driving world model with high fidelity and versatile controllability
Shenyuan Gao, Jiazhi Yang, Li Chen, Kashyap Chitta, Yihang Qiu, Andreas Geiger, Jun Zhang, and Hongyang Li · 2024
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Hivt: Hierarchical vector transformer for multi-agent motion prediction
Zikang Zhou, Luyao Ye, Jianping Wang, Kui Wu, and Kejie Lu · 2022
Cited alongside, same era.
Is conditional generative modeling all you need for decision making?
Anurag Ajay, Yilun Du, Abhi Gupta, Joshua B. Tenenbaum, Tommi S. Jaakkola, and Pulkit Agrawal · 2023
Cited alongside, same era.
Polydiffuse: Polygonal shape reconstruction via guided set diffusion models
Jiacheng Chen, Ruizhi Deng, and Yasutaka Furukawa · 2023
Cited alongside, same era.
Trafficgen: Learning to generate diverse and realistic traffic scenarios
Lan Feng, Quanyi Li, Zhenghao Peng, Shuhan Tan, and Bolei Zhou · 2023
Cited alongside, same era.
Waymax: An accelerated, data-driven simulator for large-scale autonomous driving research
Cole Gulino, Justin Fu, Wenjie Luo, George Tucker, Eli Bronstein, Yiren Lu, Jean Harb, Xinlei Pan, Yan Wang, Xiangyu Chen, John D. Co-Reyes, Rishabh Agarwal, Rebecca Roelofs, Yao Lu, Nico Montali, Paul Mougin, Zoey Yang, Brandyn White, Aleksandra Faust, Rowan McAllister, Dragomir Anguelov, and Benjamin Sapp · 2023
Cited alongside, same era.
Scenedm: Scene-level multi-agent trajectory generation with consistent diffusion models
Zhiming Guo, Xing Gao, Jianlan Zhou, Xinyu Cai, and Botian Shi · 2023
Cited alongside, same era.
GAIA-1: A generative world model for autonomous driving
Anthony Hu, Lloyd Russell, Hudson Yeo, Zak Murez, George Fedoseev, Alex Kendall, Jamie Shotton, and Gianluca Corrado · 2023
Cited alongside, same era.
Solving motion planning tasks with a scalable generative model
Yihan Hu, Siqi Chai, Zhening Yang, Jingyu Qian, Kun Li, Wenxin Shao, Haichao Zhang, Wei Xu, and Qiang Liu · 2024
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Versatile behavior diffusion for generalized traffic agent simulation
Zhiyu Huang, Zixu Zhang, Ameya Vaidya, Yuxiao Chen, Chen Lv, and Jaime Fernández Fisac · 2024
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Scenediffuser: Efficient and controllable driving simulation initialization and rollout
Chiyu Max Jiang, Yijing Bai, Andre Cornman, Christopher Davis, Xiukun Huang, Hong Jeon, Sakshum Kulshrestha, John Wheatley Lambert, Shuangyu Li, Xuanyu Zhou, Carlos Fuertes, Chang Yuan, Mingxing Tan, Yin Zhou, and Dragomir Anguelov · 2024
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Towards learning-based planning: The nuplan benchmark for real-world autonomous driving
Napat Karnchanachari, Dimitris Geromichalos, Kok Seang Tan, Nanxiang Li, Christopher Eriksen, Shakiba Yaghoubi, Noushin Mehdipour, Gianmarco Bernasconi, Whye Kit Fong, Yiluan Guo, and Holger Caesar · 2024
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Torchdriveenv: A reinforcement learning benchmark for autonomous driving with reactive, realistic, and diverse non-playable characters
Jonathan Wilder Lavington, Ke Zhang, Vasileios Lioutas, Matthew Niedoba, Yunpeng Liu, Dylan Green, Saeid Naderiparizi, Xiaoxuan Liang, Setareh Dabiri, Adam Ścibior, Berend Zwartsenberg, and Frank Wood · 2024
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Choose your simulator wisely: A review on open-source simulators for autonomous driving
Yueyuan Li, Wei Yuan, Songan Zhang, Weihao Yan, Qiyuan Shen, Chunxiang Wang, and Ming Yang · 2024
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Neuroncap: Photorealistic closed-loop safety testing for autonomous driving
William Ljungbergh, Adam Tonderski, Joakim Johnander, Holger Caesar, Kalle Åström, Michael Felsberg, and Christoffer Petersson · 2024
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Scenecontrol: Diffusion for controllable traffic scene generation
Jack Lu, Kelvin Wong, Chris Zhang, Simon Suo, and Raquel Urtasun · 2024
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Unigen: Unified modeling of initial agent states and trajectories for generating autonomous driving scenarios
Reza Mahjourian, Rongbing Mu, Valerii Likhosherstov, Paul Mougin, Xiukun Huang, João V. Messias, and Shimon Whiteson · 2024
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Trajeglish: Traffic modeling as next-token prediction
Jonah Philion, Xue Bin Peng, and Sanja Fidler · 2024
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CtRL-sim: Reactive and controllable driving agents with offline reinforcement learning
Luke Rowe, Roger Girgis, Anthony Gosselin, Bruno Carrez, Florian Golemo, Felix Heide, Liam Paull, and Christopher Pal · 2024
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Drivescenegen: Generating diverse and realistic driving scenarios from scratch
Shuo Sun, Zekai Gu, Tianchen Sun, Jiawei Sun, Chengran Yuan, Yuhang Han, Dongen Li, and Marcelo H. Ang · 2024
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Neurad: Neural rendering for autonomous driving
Adam Tonderski, Carl Lindström, Georg Hess, William Ljungbergh, Lennart Svensson, and Christoffer Petersson · 2024
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Street gaussians for modeling dynamic urban scenes
Yunzhi Yan, Haotong Lin, Chenxu Zhou, Weijie Wang, Haiyang Sun, Kun Zhan, Xianpeng Lang, Xiaowei Zhou, and Sida Peng · 2024
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Adaptive diffusion terrain generator for autonomous uneven terrain navigation
Youwei Yu, Junhong Xu, and Lantao Liu · 2024
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S-nerf++: Autonomous driving simulation via neural reconstruction and generation
Yurui Chen, Junge Zhang, Ziyang Xie, Wenye Li, Feihu Zhang, Jiachen Lu, and Li Zhang · 2025
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GPUDrive: Data-driven, multi-agent driving simulation at 1 million FPS
Saman Kazemkhani, Aarav Pandya, Daphne Cornelisse, Brennan Shacklett, and Eugene Vinitsky · 2025
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Maptrv2: An end-to-end framework for online vectorized HD map construction
Bencheng Liao, Shaoyu Chen, Yunchi Zhang, Bo Jiang, Qian Zhang, Wenyu Liu, Chang Huang, and Xinggang Wang · 2025
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Diffusion models are real-time game engines
Dani Valevski, Yaniv Leviathan, Moab Arar, and Shlomi Fruchter · 2025
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