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Achieving human-like driving behaviors in complex open-world environments is a critical challenge in autonomous driving.
A perception‐driven autonomous urban vehicle
John J. Leonard, Jonathan P. How, Seth J. Teller, Mitch Berger, Stefan Campbell, Gaston A. Fiore, Luke Fletcher, Emilio Frazzoli, Albert S. Huang, Sertac Karaman, Olivier Koch, Yoshiaki Kuwata, David C. Moore, Edwin Olson, Steven C. Peters, Justin Teo, Robert Truax, Matthew R. Walter, David Barrett, Alexander K Epstein, Keoni Maheloni, Katy Moyer, Troy Jones, Ryan Buckley, Matthew E. Antone, Robert Galejs, Siddhartha Krishnamurthy, and Jonathan Williams · 2008
Earlier work this paper cites.
Autonomous driving in urban environments: Boss and the urban challenge
Chris Urmson, Joshua Anhalt, J. Andrew Bagnell, Christopher R. Baker, Robert Bittner, M. N. Clark, John M. Dolan, David Duggins, Tugrul Galatali, Christopher Geyer, Michele Gittleman, Sam Harbaugh, Martial Hebert, Thomas M. Howard, Sascha Kolski, Alonzo Kelly, Maxim Likhachev, Matthew McNaughton, Nick Miller, Kevin M. Peterson, Brian Pilnick, Ragunathan Raj Rajkumar, Paul E. Rybski, Bryan Salesky, Young-Woo Seo, Sanjiv Singh, Jarrod M. Snider, Anthony Stentz, William Whittaker, Ziv Wolkowicki, Jason Ziglar, Hong Bae, Thomas Brown, Daniel Demitrish, Bakhtiar Litkouhi, James N. Nickolaou, Varsha Sadekar, Wende Zhang, Joshua Struble, Michael Taylor, Michael Darms, and Dave Ferguson · 2008
Earlier work this paper cites.
Deep unsupervised learning using nonequilibrium thermodynamics, 2015
Jascha Sohl-Dickstein, Eric A. Weiss, Niru Maheswaranathan, and Surya Ganguli · 2015
Earlier work this paper cites.
End to end learning for self-driving cars
Mariusz Bojarski, Davide Del Testa, Daniel Dworakowski, Bernhard Firner, Beat Flepp, Prasoon Goyal, Lawrence D Jackel, Mathew Monfort, Urs Muller, Jiakai Zhang, et al · 2016
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Chauffeurnet: Learning to drive by imitating the best and synthesizing the worst
Mayank Bansal, Alex Krizhevsky, and Abhijit Ogale · 2018
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Baidu apollo em motion planner, 2018
Haoyang Fan, Fan Zhu, Changchun Liu, Liangliang Zhang, Li Zhuang, Dong Li, Weicheng Zhu, Jiangtao Hu, Hongye Li, and Qi Kong · 2018
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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 · 2019
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Learning to drive in a day
Alex Kendall, Jeffrey Hawke, David Janz, Przemyslaw Mazur, Daniele Reda, John-Mark Allen, Vinh-Dieu Lam, Alex Bewley, and Amar Shah · 2019
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Generative modeling by estimating gradients of the data distribution
Yang Song and Stefano Ermon · 2019
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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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Urban driving with conditional imitation learning
Jeffrey Hawke, Richard Shen, Corina Gurau, Siddharth Sharma, Daniele Reda, Nikolay Nikolov, Przemysław Mazur, Sean Micklethwaite, Nicolas Griffiths, Amar Shah, et al · 2020
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Denoising diffusion probabilistic models
Jonathan Ho, Ajay Jain, and Pieter Abbeel · 2020
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Deep learning for safe autonomous driving: Current challenges and future directions
Khan Muhammad, Amin Ullah, Jaime Lloret, Javier Del Ser, and Victor Hugo C de Albuquerque · 2020
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A survey of end-to-end driving: Architectures and training methods
Ardi Tampuu, Tambet Matiisen, Maksym Semikin, Dmytro Fishman, and Naveed Muhammad · 2020
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nuplan: A closed-loop ml-based planning benchmark for autonomous vehicles
Holger Caesar, Juraj Kabzan, Kok Seang Tan, Whye Kit Fong, Eric Wolff, Alex Lang, Luke Fletcher, Oscar Beijbom, and Sammy Omari · 2021
Earlier work this paper cites.
Learning to drive from a world on rails
Dian Chen, Vladlen Koltun, and Philipp Krähenbühl · 2021
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Diffusion models beat gans on image synthesis
Prafulla Dhariwal and Alexander Nichol · 2021
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Scene transformer: A unified architecture for predicting multiple agent trajectories
Jiquan Ngiam, Benjamin Caine, Vijay Vasudevan, Zhengdong Zhang, Hao-Tien Lewis Chiang, Jeffrey Ling, Rebecca Roelofs, Alex Bewley, Chenxi Liu, Ashish Venugopal, et al · 2021
Cited alongside, same era.
Urban driver: Learning to drive from real-world demonstrations using policy gradients, 2021
Oliver Scheel, Luca Bergamini, Maciej Wołczyk, Błażej Osiński, and Peter Ondruska · 2021
Cited alongside, same era.
Score-based generative modeling through stochastic differential equations, 2021
Yang Song, Jascha Sohl-Dickstein, Diederik P. Kingma, Abhishek Kumar, Stefano Ermon, and Ben Poole · 2021
Cited alongside, same era.
Mlp-mixer: An all-mlp architecture for vision
Ilya O Tolstikhin, Neil Houlsby, Alexander Kolesnikov, Lucas Beyer, Xiaohua Zhai, Thomas Unterthiner, Jessica Yung, Andreas Steiner, Daniel Keysers, Jakob Uszkoreit, et al · 2021
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 · 2022
Cheng Lu, Huayu Chen, Jianfei Chen, Hang Su, Chongxuan Li, and Jun Zhu · 2023
Later among the works it cites.
On distillation of guided diffusion models
Chenlin Meng, Robin Rombach, Ruiqi Gao, Diederik Kingma, Stefano Ermon, Jonathan Ho, and Tim Salimans · 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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Scalable diffusion models with transformers
William Peebles and Saining Xie · 2023
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Yang Song, Prafulla Dhariwal, Mark Chen, and Ilya Sutskever · 2023
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Cited alongside, same era.
Transfuser: Imitation with transformer-based sensor fusion for autonomous driving
Kashyap Chitta, Aditya Prakash, Bernhard Jaeger, Zehao Yu, Katrin Renz, and Andreas Geiger · 2022
Cited alongside, same era.
Diffusion posterior sampling for general noisy inverse problems
Hyungjin Chung, Jeongsol Kim, Michael T Mccann, Marc L Klasky, and Jong Chul Ye · 2022
Cited alongside, same era.
Planning with diffusion for flexible behavior synthesis
Michael Janner, Yilun Du, Joshua Tenenbaum, and Sergey Levine · 2022
Cited alongside, same era.
Dpm-solver: A fast ode solver for diffusion probabilistic model sampling in around 10 steps
Cheng Lu, Yuhao Zhou, Fan Bao, Jianfei Chen, Chongxuan Li, and Jun Zhu · 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.
Safetynet: Safe planning for real-world self-driving vehicles using machine-learned policies
Matt Vitelli, Yan Chang, Yawei Ye, Ana Ferreira, Maciej Wołczyk, Błażej Osiński, Moritz Niendorf, Hugo Grimmett, Qiangui Huang, Ashesh Jain, et al · 2022
Cited alongside, same era.
End-to-end autonomous driving: Challenges and frontiers
Li Chen, Penghao Wu, Kashyap Chitta, Bernhard Jaeger, Andreas Geiger, and Hongyang Li · 2023
Cited alongside, same era.
Qiao Sun, Shiduo Zhang, Danjiao Ma, Jingzhe Shi, Derun Li, Simian Luo, Yu Wang, Ningyi Xu, Guangzhi Cao, and Hang Zhao · 2023
Later among the works it cites.
Guided conditional diffusion for controllable traffic simulation
Ziyuan Zhong, Davis Rempe, Danfei Xu, Yuxiao Chen, Sushant Veer, Tong Che, Baishakhi Ray, and Marco Pavone · 2023
Later among the works it cites.
Query-centric trajectory prediction
Zikang Zhou, Jianping Wang, Yung-Hui Li, and Yu-Kai Huang · 2023
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Pluto: Pushing the limit of imitation learning-based planning for autonomous driving
Jie Cheng, Yingbing Chen, and Qifeng Chen · 2024
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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
Later among the works it cites.
Is ego status all you need for open-loop end-to-end autonomous driving?
Zhiqi Li, Zhiding Yu, Shiyi Lan, Jiahan Li, Jan Kautz, Tong Lu, and Jose M Alvarez · 2024
Later among the works it cites.
Generalizing motion planners with mixture of experts for autonomous driving
Qiao Sun, Huimin Wang, Jiahao Zhan, Fan Nie, Xin Wen, Leimeng Xu, Kun Zhan, Peng Jia, Xianpeng Lang, and Hang Zhao · 2024
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Brian Yang, Huangyuan Su, Nikolaos Gkanatsios, Tsung-Wei Ke, Ayush Jain, Jeff Schneider, and Katerina Fragkiadaki · 2024
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Safe offline reinforcement learning with feasibility-guided diffusion model
Yinan Zheng, Jianxiong Li, Dongjie Yu, Yujie Yang, Shengbo Eben Li, Xianyuan Zhan, and Jingjing Liu · 2024
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Skill expansion and composition in parameter space
Tenglong Liu, Jianxiong Li, Yinan Zheng, Haoyi Niu, Yixing Lan, Xin Xu, and Xianyuan Zhan · 2025
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Rethinking diffusion posterior sampling: From conditional score estimator to maximizing a posterior
Tongda Xu, Jian Li, Xinjie Zhang, Xingtong Ge, Dailan He, Xiyan Cai, Ming Sun, Yan Wang, Jingjing Liu, and Ya-Qin Zhang · 2025
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