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Simulation with realistic, interactive agents represents a key task for autonomous vehicle software development.
Remarks on some nonparametric estimates of a density function
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Alvinn: An autonomous land vehicle in a neural network
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Sumo (simulation of urban mobility)-an open-source traffic simulation
Daniel Krajzewicz, Georg Hertkorn, Christian Rössel, and Peter Wagner · 2002
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A reduction of imitation learning and structured prediction to no-regret online learning
Stephane Ross, Geoffrey Gordon, and Drew Bagnell · 2011
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Are we ready for autonomous driving? the kitti vision benchmark suite
Andreas Geiger, Philip Lenz, and Raquel Urtasun · 2012
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f-gan: Training generative neural samplers using variational divergence minimization
Sebastian Nowozin, Botond Cseke, and Ryota Tomioka · 2016
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Improved techniques for training gans
Tim Salimans, Ian Goodfellow, Wojciech Zaremba, Vicki Cheung, Alec Radford, and Xi Chen · 2016
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CARLA: An open urban driving simulator
Alexey Dosovitskiy, German Ros, Felipe Codevilla, Antonio Lopez, and Vladlen Koltun · 2017
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Gans trained by a two time-scale update rule converge to a local nash equilibrium
Martin Heusel, Hubert Ramsauer, Thomas Unterthiner, Bernhard Nessler, and Sepp Hochreiter · 2017
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Ł ukasz Kaiser, and Illia Polosukhin · 2017
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Flow: Architecture and benchmarking for reinforcement learning in traffic control
Cathy Wu, Aboudy Kreidieh, Kanaad Parvate, Eugene Vinitsky, and Alexandre M Bayen · 2017
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A survey of statistical model checking
Gul Agha and Karl Palmskog · 2018
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Multi-agent imitation learning for driving simulation
Raunak P Bhattacharyya, Derek J Phillips, Blake Wulfe, Jeremy Morton, Alex Kuefler, and Mykel J Kochenderfer · 2018
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End-to-end driving via conditional imitation learning
Felipe Codevilla, Matthias Müller, Antonio López, Vladlen Koltun, and Alexey Dosovitskiy · 2018
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Convolutional social pooling for vehicle trajectory prediction
Nachiket Deo and Mohan M. Trivedi · 2018
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ChauffeurNet: Learning to drive by imitating the best and synthesizing the worst
Mayank Bansal, Alex Krizhevsky, and Abhijit S. Ogale · 2019
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Argoverse: 3d tracking and forecasting with rich maps
Ming-Fang Chang, John Lambert, Patsorn Sangkloy, Jagjeet Singh, Slawomir Bak, Andrew Hartnett, De Wang, Peter Carr, Simon Lucey, Deva Ramanan, and James Hays · 2019
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The trajectron: Probabilistic multi-agent trajectory modeling with dynamic spatiotemporal graphs
Boris Ivanovic and Marco Pavone · 2019
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A style-based generator architecture for generative adversarial networks
Tero Karras, Samuli Laine, and Timo Aila · 2019
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Precog: Prediction conditioned on goals in visual multi-agent settings
Nicholas Rhinehart, Rowan McAllister, Kris Kitani, and Sergey Levine · 2019
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Multiple futures prediction
Charlie Tang and Russ R Salakhutdinov · 2019
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Analyzing the variety loss in the context of probabilistic trajectory prediction
Luca Anthony Thiede and Pratik Prabhanjan Brahma · 2019
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Wei Zhan, Liting Sun, Di Wang, Haojie Shi, Aubrey Clausse, Maximilian Naumann, Julius Kümmerle, Hendrik Königshof, Christoph Stiller, Arnaud de La Fortelle, and Masayoshi Tomizuka · 2019
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BARK: Open behavior benchmarking in multi-agent environments
Julian Bernhard, Klemens Esterle, Patrick Hart, and Tobias Kessler · 2020
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nuScenes: A multimodal dataset for autonomous driving
Holger Caesar, Varun Bankiti, Alex H Lang, Sourabh Vora, Venice Erin Liong, Qiang Xu, Anush Krishnan, Yu Pan, Giancarlo Baldan, and Oscar Beijbom · 2020
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Learning by cheating
Dian Chen, Brady Zhou, Vladlen Koltun, and Philipp Krähenbühl · 2020
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Denoising diffusion probabilistic models
Jonathan Ho, Ajay Jain, and Pieter Abbeel · 2020
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Metadrive: Composing diverse driving scenarios for generalizable reinforcement learning
Quanyi Li, Zhenghao Peng, Lan Feng, Qihang Zhang, Zhenghai Xue, and Bolei Zhou · 2022
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Hierarchical text-conditional image generation with clip latents
Aditya Ramesh, Prafulla Dhariwal, Alex Nichol, Casey Chu, and Mark Chen · 2022
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Generating useful accident-prone driving scenarios via a learned traffic prior
Davis Rempe, Jonah Philion, Leonidas J Guibas, Sanja Fidler, and Or Litany · 2022
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High-resolution image synthesis with latent diffusion models
Robin Rombach, Andreas Blattmann, Dominik Lorenz, Patrick Esser, and Björn Ommer · 2022
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Photorealistic text-to-image diffusion models with deep language understanding
Chitwan Saharia, William Chan, Saurabh Saxena, Lala Li, Jay Whang, Emily Denton, Seyed Kamyar Seyed Ghasemipour, Raphael Gontijo-Lopes, Burcu Karagol Ayan, Tim Salimans, Jonathan Ho, David J. Fleet, and Mohammad Norouzi · 2022
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Analyzing and improving the image quality of stylegan
Tero Karras, Samuli Laine, Miika Aittala, Janne Hellsten, Jaakko Lehtinen, and Timo Aila · 2020
Cited alongside, same era.
Lidarsim: Realistic lidar simulation by leveraging the real world
Sivabalan Manivasagam, Shenlong Wang, Kelvin Wong, Wenyuan Zeng, Mikita Sazanovich, Shuhan Tan, Bin Yang, Wei-Chiu Ma, and Raquel Urtasun · 2020
Cited alongside, same era.
Trajectron++: Dynamically-feasible trajectory forecasting with heterogeneous data
Tim Salzmann, Boris Ivanovic, Punarjay Chakravarty, and Marco Pavone · 2020
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Scalability in perception for autonomous driving: Waymo open dataset
Pei Sun, Henrik Kretzschmar, Xerxes Dotiwalla, Aurelien Chouard, Vijaysai Patnaik, Paul Tsui, James Guo, Yin Zhou, Yuning Chai, Benjamin Caine, et al · 2020
Cited alongside, same era.
Surfelgan: Synthesizing realistic sensor data for autonomous driving
Zhenpei Yang, Yuning Chai, Dragomir Anguelov, Yin Zhou, Pei Sun, Dumitru Erhan, Sean Rafferty, and Henrik Kretzschmar · 2020
Cited alongside, same era.
Smarts: An open-source scalable multi-agent rl training school for autonomous driving
Ming Zhou, Jun Luo, Julian Villella, Yaodong Yang, David Rusu, Jiayu Miao, Weinan Zhang, Montgomery Alban, IMAN FADAKAR, Zheng Chen, Chongxi Huang, Ying Wen, Kimia Hassanzadeh, Daniel Graves, Zhengbang Zhu, Yihan Ni, Nhat Nguyen, Mohamed Elsayed, Haitham Ammar, Alexander Cowen-Rivers, Sanjeevan Ahilan, Zheng Tian, Daniel Palenicek, Kasra Rezaee, Peyman Yadmellat, Kun Shao, dong chen, Baokuan Zhang, Hongbo Zhang, Jianye Hao, Wulong Liu, and Jun Wang · 2020
Cited alongside, same era.
SimNet: Learning reactive self-driving simulations from real-world observations
Luca Bergamini, Yawei Ye, Oliver Scheel, Long Chen, Chih Hu, Luca Del Pero, Błażej Osiński, Hugo Grimmet, and Peter Ondruska · 2021
Cited alongside, same era.
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Mtr-a: 1st place solution for 2022 waymo open dataset challenge – motion prediction, 2022a
Shaoshuai Shi, Li Jiang, Dengxin Dai, and Bernt Schiele · 2022
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DiJia Su, Bertrand Douillard, Rami Al-Rfou, Cheolho Park, and Benjamin Sapp · 2022
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InterSim: Interactive traffic simulation via explicit relation modeling
Qiao Sun, Xin Huang, Brian Williams, and Hang Zhao · 2022
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Block-nerf: Scalable large scene neural view synthesis
Matthew Tancik, Vincent Casser, Xinchen Yan, Sabeek Pradhan, Ben Mildenhall, Pratul P. Srinivasan, Jonathan T. Barron, and Henrik Kretzschmar · 2022
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Multipath++: Efficient information fusion and trajectory aggregation for behavior prediction
Balakrishnan Varadarajan, Ahmed Hefny, Avikalp Srivastava, Khaled S. Refaat, Nigamaa Nayakanti, Andre Cornman, Kan Chen, Bertrand Douillard, Chi Pang Lam, Dragomir Anguelov, and Benjamin Sapp · 2022
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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
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Scaling autoregressive models for content-rich text-to-image generation
Jiahui Yu, Yuanzhong Xu, Jing Yu Koh, Thang Luong, Gunjan Baid, Zirui Wang, Vijay Vasudevan, Alexander Ku, Yinfei Yang, Burcu Karagol Ayan, Ben Hutchinson, Wei Han, Zarana Parekh, Xin Li, Han Zhang, Jason Baldridge, and Yonghui Wu · 2022
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Collision avoidance detour: A solution for 2023 waymo open dataset challenge - sim agents
Hsu-kuang Chiu and Stephen F. Smith · 2023
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Generating driving scenes with diffusion
Nick Roy Ethan Pronovost, Kai Wang · 2023
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Trafficgen: Learning to generate diverse and realistic traffic scenarios
Lan Feng, Quanyi Li, Zhenghao Peng, Shuhan Tan, and Bolei Zhou · 2023
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Imitation is not enough: Robustifying imitation with reinforcement learning for challenging driving scenarios
Yiren Lu, Justin Fu, George Tucker, Xinlei Pan, Eli Bronstein, Becca Roelofs, Benjamin Sapp, Brandyn White, Aleksandra Faust, Shimon Whiteson, et al · 2023
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Jfp: Joint future prediction with interactive multi-agent modeling for autonomous driving
Wenjie Luo, Cheol Park, Andre Cornman, Benjamin Sapp, and Dragomir Anguelov · 2023
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Wayformer: Motion forecasting via simple & efficient attention networks
Nigamaa Nayakanti, Rami Al-Rfou, Aurick Zhou, Kratarth Goel, Khaled S Refaat, and Benjamin Sapp · 2023
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A simple yet effective method for simulating realistic multi-agent behaviors
Cheng Qian, Di Xiu, and Minghao Tian · 2023
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Joint-multipath++ for simulation agents
Wenxi Wang and Haotian Zhen · 2023
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Multiverse transformer: 1st place solution for waymo open sim agents challenge 2023
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Bits: Bi-level imitation for traffic simulation
Danfei Xu, Yuxiao Chen, Boris Ivanovic, and Marco Pavone · 2023
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Learning naturalistic driving environment with statistical realism
Xintao Yan, Zhengxia Zou, Shuo Feng, Haojie Zhu, Haowei Sun, and Henry X Liu · 2023
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Trafficbots: Towards world models for autonomous driving simulation and motion prediction
Zhejun Zhang, Alexander Liniger, Dengxin Dai, Fisher Yu, and Luc Van Gool · 2023
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