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Simulation is an essential tool to develop and benchmark autonomous vehicle planning software in a safe and cost-effective manner.
Alvinn: An autonomous land vehicle in a neural network
Dean A Pomerleau · 1988
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Congested traffic states in empirical observations and microscopic simulations
Martin Treiber, Ansgar Hennecke, and Dirk Helbing · 2000
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Torcs, the open racing car simulator
Bernhard Wymann, Eric Espié, Christophe Guionneau, Christos Dimitrakakis, Rémi Coulom, and Andrew Sumner · 2000
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A reduction of imitation learning and structured prediction to no-regret online learning
Stéphane Ross, Geoffrey Gordon, and Drew Bagnell · 2011
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Tom Schaul, John Quan, Ioannis Antonoglou, and David Silver · 2015
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TensorFlow: learning functions at scale
Martín Abadi · 2016
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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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Openai gym, 2016
Greg Brockman, Vicki Cheung, Ludwig Pettersson, Jonas Schneider, John Schulman, Jie Tang, and Wojciech Zaremba · 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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Beyond grand theft auto v for training, testing and enhancing deep learning in self driving cars
Mark Martinez, Chawin Sitawarin, Kevin Finch, Lennart Meincke, Alex Yablonski, and Alain Kornhauser · 2017
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Domain randomization for transferring deep neural networks from simulation to the real world
Josh Tobin, Rachel Fong, Alex Ray, Jonas Schneider, Wojciech Zaremba, and Pieter Abbeel · 2017
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JAX: composable transformations of Python+NumPy programs, 2018
James Bradbury, Roy Frostig, Peter Hawkins, Matthew James Johnson, Chris Leary, Dougal Maclaurin, George Necula, Adam Paszke, Jake VanderPlas, Skye Wanderman-Milne, and Qiao Zhang · 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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Navigating occluded intersections with autonomous vehicles using deep reinforcement learning
David Isele, Reza Rahimi, Akansel Cosgun, Kaushik Subramanian, and Kikuo Fujimura · 2018
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An environment for autonomous driving decision-making
Edouard Leurent · 2018
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Sim4cv: A photo-realistic simulator for computer vision applications
Matthias Müller, Vincent Casser, Jean Lahoud, Neil Smith, and Bernard Ghanem · 2018
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A reinforcement learning based approach for automated lane change maneuvers
Pin Wang, Ching-Yao Chan, and Arnaud de La Fortelle · 2018
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ChauffeurNet: Learning to drive by imitating the best and synthesizing the worst
Mayank Bansal, Alex Krizhevsky, and Abhijit Ogale · 2019
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Multipath: Multiple probabilistic anchor trajectory hypotheses for behavior prediction
Yuning Chai, Benjamin Sapp, Mayank Bansal, and Dragomir Anguelov · 2019
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Causal confusion in imitation learning
Pim De Haan, Dinesh Jayaraman, and Sergey Levine · 2019
Cited alongside, same era.
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
Cited alongside, same era.
dm_env: A python interface for reinforcement learning environments, 2019
Alistair Muldal, Yotam Doron, John Aslanides, Tim Harley, Tom Ward, and Siqi Liu · 2019
Cited alongside, same era.
PRECOG: prediction conditioned on goals in visual multi-agent settings
Nicholas Rhinehart, Rowan McAllister, Kris M. Kitani, and Sergey Levine · 2019
Cited alongside, same era.
Multiple futures prediction
Charlie Tang and Russ R Salakhutdinov · 2019
Cited alongside, same era.
Summit: A simulator for urban driving in massive mixed traffic
Densetnt: End-to-end trajectory prediction from dense goal sets
Junru Gu, Chen Sun, and Hang Zhao · 2021
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Drivergym: Democratising reinforcement learning for autonomous driving
Parth Kothari, Christian Perone, Luca Bergamini, Alexandre Alahi, and Peter Ondruska · 2021
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Pods: Policy optimization via differentiable simulation
Miguel Angel Zamora Mora, Momchil Peychev, Sehoon Ha, Martin Vechev, and Stelian Coros · 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
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Madras: Multi agent driving simulator
Anirban Santara, Sohan Rudra, Sree Aditya Buridi, Meha Kaushik, Abhishek Naik, Bharat Kaul, and Balaraman Ravindran · 2021
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Panpan Cai, Yiyuan Lee, Yuanfu Luo, and David Hsu · 2020
Cited alongside, same era.
Learning by cheating
Dian Chen, Brady Zhou, Vladlen Koltun, and Philipp Krähenbühl · 2020
Cited alongside, same era.
Acme: A research framework for distributed reinforcement learning
Matthew W. Hoffman, Bobak Shahriari, John Aslanides, Gabriel Barth-Maron, Nikola Momchev, Danila Sinopalnikov, Piotr Stańczyk, Sabela Ramos, Anton Raichuk, Damien Vincent, Léonard Hussenot, Robert Dadashi, Gabriel Dulac-Arnold, Manu Orsini, Alexis Jacq, Johan Ferret, Nino Vieillard, Seyed Kamyar Seyed Ghasemipour, Sertan Girgin, Olivier Pietquin, Feryal Behbahani, Tamara Norman, Abbas Abdolmaleki, Albin Cassirer, Fan Yang, Kate Baumli, Sarah Henderson, Abe Friesen, Ruba Haroun, Alex Novikov, Sergio Gómez Colmenarejo, Serkan Cabi, Caglar Gulcehre, Tom Le Paine, Srivatsan Srinivasan, Andrew Cowie, Ziyu Wang, Bilal Piot, and Nando de Freitas · 2020
Cited alongside, same era.
Learning lane graph representations for motion forecasting
Ming Liang, Bin Yang, Rui Hu, Yun Chen, Renjie Liao, Song Feng, and Raquel Urtasun · 2020
Cited alongside, same era.
Systems and methods for generating synthetic sensor data via machine learning, Sept. 24 2020
Sivabalan Manivasagam, Shenlong Wang, Wei-Chiu Ma, Kelvin Ka Wing Wong, Wenyuan Zeng, and Raquel Urtasun · 2020
Cited alongside, same era.
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
Cited alongside, same era.
Simulation-based reinforcement learning for real-world autonomous driving
Błażej Osiński, Adam Jakubowski, Paweł Ziecina, Piotr Miłoś, Christopher Galias, Silviu Homoceanu, and Henryk Michalewski · 2020
Cited alongside, same era.
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Imagining the road ahead: Multi-agent trajectory prediction via differentiable simulation
Adam Ścibior, Vasileios Lioutas, Daniele Reda, Peyman Bateni, and Frank Wood · 2021
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Vista 2.0: An open, data-driven simulator for multimodal sensing and policy learning for autonomous vehicles
Alexander Amini, Tsun-Hsuan Wang, Igor Gilitschenski, Wilko Schwarting, Zhijian Liu, Song Han, Sertac Karaman, and Daniela Rus · 2022
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Hierarchical model-based imitation learning for planning in autonomous driving
Eli Bronstein, Mark Palatucci, Dominik Notz, Brandyn White, Alex Kuefler, Yiren Lu, Supratik Paul, Payam Nikdel, Paul Mougin, Hongge Chen, Justin Fu, Austin Abrams, Punit Shah, Evan Racah, Benjamin Frenkel, Shimon Whiteson, and Dragomir Anguelov · 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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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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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, et al · 2022
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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 · 2022
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Wayformer: Motion forecasting via simple and efficient attention networks, 2022
Nigamaa Nayakanti, Rami Al-Rfou, Aurick Zhou, Kratarth Goel, Khaled S. Refaat, and Benjamin Sapp · 2022
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Intersim: Interactive traffic simulation via explicit relation modeling
Qiao Sun, Xin Huang, Brian C 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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Eugene Vinitsky, Nathan Lichtlé, Xiaomeng Yang, Brandon Amos, and Jakob Foerster · 2022
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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
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Bits: Bi-level imitation for traffic simulation
Danfei Xu, Yuxiao Chen, Boris Ivanovic, and Marco Pavone · 2022
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Deep rl at scale: Sorting waste in office buildings with a fleet of mobile manipulators
Alexander Herzog, Kanishka Rao, Karol Hausman, Yao Lu, Paul Wohlhart, Mengyuan Yan, Jessica Lin, Montserrat Gonzalez Arenas, Ted Xiao, Daniel Kappler, et al · 2023
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