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Despite the numerous successes of machine learning over the past decade (image recognition, decision-making, NLP, image synthesis), self-driving technology has not yet followed the same trend.
Social force model for pedestrian dynamics
D. Helbing and P. Molnar · 1998
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Rrt-connect: An efficient approach to single-query path planning
J. J. K. Jr. and S. M. Lavalle · 2000
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Probabilistic Robotics (Intelligent Robotics and Autonomous Agents)
S. Thrun, W. Burgard, and D. Fox · 2005
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Navigating car-like robots in unstructured environments using an obstacle sensitive cost function
J. Ziegler, M. Werling, and J. Schroder · 2008
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Imagenet: A large-scale hierarchical image database
J. Deng, W. Dong, R. Socher, L.-J. Li, K. Li, and L. Fei-Fei · 2009
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Junior: The Stanford Entry in the Urban Challenge
M. Montemerlo, J. Becker, S. Bhat, H. Dahlkamp, D. Dolgov, S. Ettinger, D. Haehnel, T. Hilden, G. Hoffmann, B. Huhnke, D. Johnston, S. Klumpp, D. Langer, A. Levandowski, J. Levinson, J. Marcil, D. Orenstein, J. Paefgen, I. Penny, A. Petrovskaya, M. Pflueger, G. Stanek, D. Stavens, A. Vogt, and S. Thrun · 2009
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The darpa urban challenge
Buehler · 2009
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A reduction of imitation learning and structured prediction to no-regret online learning
S. Ross, G. Gordon, and D. Bagnell · 2011
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https://www.youtube.com/watch?v=BEjxQd219is , 2012
Sergey Brin predicts self driving vehicles are five years away · 2012
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Playing atari with deep reinforcement learning
V. Mnih, K. Kavukcuoglu, D. Silver, A. Graves, I. Antonoglou, D. Wierstra, and M. Riedmiller · 2013
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Intention-aware motion planning
T. Bandyopadhyay, K. S. Won, E. Frazzoli, D. Hsu, W. S. Lee, and D. Rus · 2013
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Vision meets robotics: The kitti dataset
A. Geiger, P. Lenz, C. Stiller, and R. Urtasun · 2013
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A multi-sensor fusion system for moving object detection and tracking in urban driving environments
H. Cho, Y.-W. Seo, B. V. Kumar, and R. R. Rajkumar · 2014
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https://techcrunch.com/2015/10/06/elon-musk-sam-altman-say-self-driving-cars-are-going-to-be-on-the-road-in-just-a-few-years/ , 2015
Sam Altman predicts self driving vehicles are four years away · 2015
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https://www.zdnet.com/article/ford-self-driving-cars-are-five-years-away-from-changing-the-world/ , 2016
Ford autonomy team predicts self driving vehicles are five years away · 2016
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Pointnet: Deep learning on point sets for 3d classification and segmentation, 2016
C. R. Qi, H. Su, K. Mo, and L. J. Guibas · 2016
Cited alongside, same era.
Mastering the game of go with deep neural networks and tree search
D. Silver, A. Huang, C. Maddison, A. Guez, L. Sifre, G. Driessche, J. Schrittwieser, I. Antonoglou, V. Panneershelvam, M. Lanctot, S. Dieleman, D. Grewe, J. Nham, N. Kalchbrenner, I. Sutskever, T. Lillicrap, M. Leach, K. Kavukcuoglu, T. Graepel, and D. Hassabis · 2016
Cited alongside, same era.
Generative adversarial imitation learning
J. Ho and S. Ermon · 2016
Cited alongside, same era.
Ssd-6d: Making rgb-based 3d detection and 6d pose estimation great again
W. Kehl, F. Manhardt, F. Tombari, S. Ilic, and N. Navab · 2017
Cited alongside, same era.
Desire: Distant future prediction in dynamic scenes with interacting agents
N. Lee, W. Choi, P. Vernaza, C. Choy, P. H. S. Torr, and M. Chandraker · 2017
Cited alongside, same era.
Chauffeurnet: Learning to drive by imitating the best and synthesizing the worst, 2019
M. Bansal, A. Krizhevsky, and A. Ogale · 2019
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Causal confusion in imitation learning
P. de Haan, D. Jayaraman, and S. Levine · 2019
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Pseudo-lidar from visual depth estimation: Bridging the gap in 3d object detection for autonomous driving
Y. Wang, W.-L. Chao, D. Garg, B. Hariharan, M. Campbell, and K. Q. Weinberger · 2019
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Pointpillars: Fast encoders for object detection from point clouds
A. H. Lang, S. Vora, H. Caesar, L. Zhou, J. Yang, and O. Beijbom · 2019
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Mastering atari, go, chess and shogi by planning with a learned model
J. Schrittwieser, I. Antonoglou, T. Hubert, K. Simonyan, L. Sifre, S. Schmitt, A. Guez, E. Lockhart, D. Hassabis, T. Graepel, T. Lillicrap, and D. Silver · 2020
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A. Dosovitskiy, G. Ros, F. Codevilla, A. Lopez, and V. Koltun · 2017
Cited alongside, same era.
CARLA: An open urban driving simulator
A. Dosovitskiy, G. Ros, F. Codevilla, A. Lopez, and V. Koltun · 2017
Cited alongside, same era.
Voxelnet: End-to-end learning for point cloud based 3d object detection
Y. Zhou and O. Tuzel · 2018
Cited alongside, same era.
Sensors and sensor fusion in autonomous vehicles
J. Kocić, N. Jovičić, and V. Drndarević · 2018
Cited alongside, same era.
A general reinforcement learning algorithm that masters chess, shogi, and go through self-play
D. Silver, T. Hubert, J. Schrittwieser, I. Antonoglou, M. Lai, A. Guez, M. Lanctot, L. Sifre, D. Kumaran, T. Graepel, T. Lillicrap, K. Simonyan, and D. Hassabis · 2018
Cited alongside, same era.
Deep learning based 3d object detection for automotive radar and camera
M. Meyer and G. Kuschk · 2019
Cited alongside, same era.
Lyft level 5 perception dataset 2020
R. Kesten, M. Usman, J. Houston, T. Pandya, K. Nadhamuni, A. Ferreira, M. Yuan, B. Low, A. Jain, P. Ondruska, S. Omari, S. Shah, A. Kulkarni, A. Kazakova, C. Tao, L. Platinsky, W. Jiang, and V. Shet · 2019
Cited alongside, same era.
J. Houston, G. Zuidhof, L. Bergamini, Y. Ye, L. Chen, A. Jain, S. Omari, V. Iglovikov, and P. Ondruska · 2020
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Dsgn: Deep stereo geometry network for 3d object detection
Y. Chen, S. Liu, X. Shen, and J. Jia · 2020
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Learning to evaluate perception models using planner-centric metrics
J. Philion, A. Kar, and S. Fidler · 2020
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Divide-and-conquer for lane-aware diverse trajectory prediction, 2021
S. N N, R. Moslemi, F. Pittaluga, B. Liu, and M. Chandraker · 2021
Closest in time.
Simnet: Learning reactive self-driving simulations from real-world observations, 2021
L. Bergamini, Y. Ye, O. Scheel, L. Chen, C. Hu, L. D. Pero, B. Osinski, H. Grimmett, and P. Ondruska · 2021
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Contingencies from observations: Tractable contingency planning with learned behavior models, 04 2021
N. Rhinehart, J. He, C. Packer, M. Wright, R. McAllister, J. Gonzalez, and S. Levine · 2021
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Trafficsim: Learning to simulate realistic multi-agent behaviors
S. Suo, S. Regalado, S. Casas, and R. Urtasun · 2021
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M3dssd: Monocular 3d single stage object detector
S. Luo, H. Dai, L. Shao, and Y. Ding · 2021
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What data do we need for training an av motion planner?, 2021
L. Chen, L. Platinsky, S. Speichert, B. Osinski, O. Scheel, Y. Ye, H. Grimmett, L. del Pero, and P. Ondruska · 2021
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