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In this paper, we present a system to train driving policies from experiences collected not just from the ego-vehicle, but all vehicles that it observes.
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Map-based precision vehicle localization in urban environments
Jesse Levinson, Michael Montemerlo, and Sebastian Thrun · 2007
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Odin: Team victortango’s entry in the darpa urban challenge
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Practical search techniques in path planning for autonomous driving
Dmitri Dolgov, Sebastian Thrun, Michael Montemerlo, and James Diebel · 2008
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A perception-driven autonomous urban vehicle
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Autonomous driving in urban environments: Boss and the urban challenge
Chris Urmson, Joshua Anhalt, Drew Bagnell, Christopher Baker, Robert Bittner, MN Clark, John Dolan, Dave Duggins, Tugrul Galatali, Chris Geyer, et al · 2008
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Deepdriving: Learning affordance for direct perception in autonomous driving
Chenyi Chen, Ari Seff, Alain Kornhauser, and Jianxiong Xiao · 2015
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Batch normalization: Accelerating deep network training by reducing internal covariate shift
Sergey Ioffe and Christian Szegedy · 2015
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Learning phrase representations using rnn encoder–decoder for statistical machine translation
Kyunghyun Cho, Bart van Merriënboer Caglar Gulcehre, Dzmitry Bahdanau, Fethi Bougares Holger Schwenk, and Yoshua Bengio · 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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Desire: Distant future prediction in dynamic scenes with interacting agents
Namhoon Lee, Wongun Choi, Paul Vernaza, Christopher B Choy, Philip HS Torr, and Manmohan Chandraker · 2017
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Erfnet: Efficient residual factorized convnet for real-time semantic segmentation
Eduardo Romera, José M Alvarez, Luis M Bergasa, and Roberto Arroyo · 2017
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Rates of motor vehicle crashes, injuries and deaths in relation to driver age, united states, 2014-2015
Brian Tefft · 2017
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High definition map-based vehicle localization for highly automated driving: Geometric analysis
Shuran Zheng and Jinling Wang · 2017
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Intentnet: Learning to predict intention from raw sensor data
Sergio Casas, Wenjie Luo, and Raquel Urtasun · 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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Deep continuous fusion for multi-sensor 3d object detection
Ming Liang, Bin Yang, Shenlong Wang, and Raquel Urtasun · 2018
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Microscopic traffic simulation using sumo
Pablo Alvarez Lopez, Michael Behrisch, Laura Bieker-Walz, Jakob Erdmann, Yun-Pang Flötteröd, Robert Hilbrich, Leonhard Lücken, Johannes Rummel, Peter Wagner, and Evamarie Wießner · 2018
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Fast and furious: Real time end-to-end 3d detection, tracking and motion forecasting with a single convolutional net
Wenjie Luo, Bin Yang, and Raquel Urtasun · 2018
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Conditional affordance learning for driving in urban environments
Axel Sauer, Nikolay Savinov, and Andreas Geiger · 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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Learning by cheating
Dian Chen, Brady Zhou, Vladlen Koltun, and Philipp Krähenbühl · 2019
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3d-lanenet: end-to-end 3d multiple lane detection
Noa Garnett, Rafi Cohen, Tomer Pe’er, Roee Lahav, and Dan Levi · 2019
Tracking objects as points
Xingyi Zhou, Vladlen Koltun, and Philipp Krähenbühl · 2020
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End-to-end multi-view fusion for 3d object detection in lidar point clouds
Yin Zhou, Pei Sun, Yu Zhang, Dragomir Anguelov, Jiyang Gao, Tom Ouyang, James Guo, Jiquan Ngiam, and Vijay Vasudevan · 2020
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https://leaderboard.carla.org/leaderboard/ , 2021
Carla autonomous driving leaderboard (accessed november 2021) · 2021
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urlhttps://kait0.github.io/files/master_thesis_bernhard_jaeger.pdf, 2021
Expert drivers for autonomous driving · 2021
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Mp3: A unified model to map, perceive, predict and plan
Sergio Casas, Abbas Sadat, and Raquel Urtasun · 2021
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GRI: general reinforced imitation and its application to vision-based autonomous driving
Raphael Chekroun, Marin Toromanoff, Sascha Hornauer, and Fabien Moutarde · 2021
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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.
Pointpillars: Fast encoders for object detection from point clouds
Alex H Lang, Sourabh Vora, Holger Caesar, Lubing Zhou, Jiong Yang, and Oscar Beijbom · 2019
Cited alongside, same era.
Exploiting sparse semantic hd maps for self-driving vehicle localization
Wei-Chiu Ma, Ignacio Tartavull, Ioan Andrei Bârsan, Shenlong Wang, Min Bai, Gellert Mattyus, Namdar Homayounfar, Shrinidhi Kowshika Lakshmikanth, Andrei Pokrovsky, and Raquel Urtasun · 2019
Cited alongside, same era.
End-to-end interpretable neural motion planner
Wenyuan Zeng, Wenjie Luo, Simon Suo, Abbas Sadat, Bin Yang, Sergio Casas, and Raquel Urtasun · 2019
Cited alongside, same era.
Xingyi Zhou, Dequan Wang, and Philipp Krähenbühl · 2019
Cited alongside, same era.
Strobe: Streaming object detection from lidar packets
Davi Frossard, Simon Suo, Sergio Casas, James Tu, Rui Hu, and Raquel Urtasun · 2020
Cited alongside, same era.
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Learning to drive from a world on rails
Dian Chen, Vladlen Koltun, and Philipp Krähenbühl · 2021
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Neat: Neural attention fields for end-to-end autonomous driving
Kashyap Chitta, Aditya Prakash, and Andreas Geiger · 2021
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Lookout: Diverse multi-future prediction and planning for self-driving
Alexander Cui, Sergio Casas, Abbas Sadat, Renjie Liao, and Raquel Urtasun · 2021
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Angelos Filos, Clare Lyle, Yarin Gal, Sergey Levine, Natasha Jaques, and Gregory Farquhar · 2021
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Fiery: Future instance prediction in bird’s-eye view from surround monocular cameras
Anthony Hu, Zak Murez, Nikhil Mohan, Sofía Dudas, Jeff Hawke, Vijay Badrinarayanan, Roberto Cipolla, and Alex Kendall · 2021
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Alexey Kamenev, Lirui Wang, Ollin Boer Bohan, Ishwar Kulkarni, Bilal Kartal, Artem Molchanov, Stan Birchfield, David Nistér, and Nikolai Smolyanskiy · 2021
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Hdmapnet: An online hd map construction and evaluation framework
Qi Li, Yue Wang, Yilun Wang, and Hang Zhao · 2021
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Learning to simulate self-driven particles system with coordinated policy optimization
Zhenghao Peng, Quanyi Li, Ka Ming Hui, Chunxiao Liu, and Bolei Zhou · 2021
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Multi-modal fusion transformer for end-to-end autonomous driving
Aditya Prakash, Kashyap Chitta, and Andreas Geiger · 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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Center-based 3d object detection and tracking
Tianwei Yin, Xingyi Zhou, and Philipp Krahenbuhl · 2021
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Learning by watching
Jimuyang Zhang and Eshed Ohn-Bar · 2021
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