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Existing research on autonomous driving primarily focuses on urban driving, which is insufficient for characterising the complex driving behaviour underlying high-speed racing.
Iterative linear quadratic regulator design for nonlinear biological movement systems
Weiwei Li and Emanuel Todorov · 2004
Earlier work this paper cites.
A robust and sensitive metric for quantifying movement smoothness
S. Balasubramanian, A. Melendez-Calderon, and E. Burdet · 2012
Earlier work this paper cites.
Mujoco: A physics engine for model-based control
E. Todorov, T. Erez, and Y. Tassa · 2012
Earlier work this paper cites.
Simulated car racing championship: Competition software manual
D. Loiacono, L. Cardamone, and P. L. Lanzi · 2013
Earlier work this paper cites.
Auto-Encoding Variational Bayes
D. P. Kingma and M. Welling · 2014
Earlier work this paper cites.
A comprehensive survey on safe reinforcement learning
Javier Garcıa and Fernando Fernández · 2015
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Kinematic and dynamic vehicle models for autonomous driving control design
Jason Kong, Mark Pfeiffer, Georg Schildbach, and Francesco Borrelli · 2015
Earlier work this paper cites.
Openai gym, 2016
G. Brockman, V. Cheung, L. Pettersson, J. Schneider, J. Schulman, J. Tang, and W. Zaremba · 2016
Earlier work this paper cites.
Openai baselines
P. Dhariwal, C. Hesse, O. Klimov, A. Nichol, M. Plappert, A. Radford, J. Schulman, S. Sidor, Y. Wu, and P. Zhokhov · 2017
Earlier work this paper cites.
CARLA: An open urban driving simulator
Alexey Dosovitskiy, German Ros, Felipe Codevilla, Antonio Lopez, and Vladlen Koltun · 2017
Earlier work this paper cites.
Duckietown: An open, inexpensive and flexible platform for autonomy education and research
L. Paull, J. Tani, H. Ahn, J. Alonso-Mora, L. Carlone, M. Cap, Y. F. Chen, C. Choi, J. Dusek, Y. Fang, D. Hoehener, S. Liu, M. Novitzky, I. F. Okuyama, J. Pazis, G. Rosman, V. Varricchio, H. Wang, D. Yershov, H. Zhao, M. Benjamin, C. Carr, M. Zuber, S. Karaman, E. Frazzoli, D. Del Vecchio, D. Rus, J. How, J. Leonard, and A. Censi · 2017
Earlier work this paper cites.
Differentiable mpc for end-to-end planning and control
Brandon Amos, Ivan Dario Jimenez Rodriguez, Jacob Sacks, Byron Boots, and J Zico Kolter · 2018
Cited alongside, same era.
Duckietown environments for openai gym
M. Chevalier-Boisvert, F. Golemo, Y. Cao, B. Mehta, and L. Paull · 2018
Cited alongside, same era.
End-to-end driving via conditional imitation learning
Felipe Codevilla, Matthias M”uller, Antonio L’opez, Vladlen Koltun, and Alexey Dosovitskiy · 2018
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Soft actor-critic: Off-policy maximum entropy deep reinforcement learning with a stochastic actor
T. Haarnoja, A. Zhou, P. Abbeel, and S. Levine · 2018
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Deepmind control suite, 2018
Y. Tassa, Y. Doron, A. Muldal, T. Erez, Y. Li, D. de Las Casas, D. Budden, A. Abdolmaleki, J. Merel, A. Lefrancq, T. Lillicrap, and M. Riedmiller · 2018
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Super-human performance in gran turismo sport using deep reinforcement learning, 2020
F. Florian, S. Yunlong, E. Kaufmann, D. Scaramuzza, and P. Duerr · 2020
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Confidence-aware motion prediction for real-time collision avoidance1
David Fridovich-Keil, Andrea Bajcsy, Jaime F Fisac, Sylvia L Herbert, Steven Wang, Anca D Dragan, and Claire J Tomlin · 2020
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Minimum race-time planning-strategy for an autonomous electric racecar
T. Herrmann, F. Passigato, J. Betz, and M. Lienkamp · 2020
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Real-time adaptive velocity optimization for autonomous electric cars at the limits of handling
T. Herrmann, A. Wischnewski, L. Hermansdorfer, J. Betz, and M. Lienkamp · 2020
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Diverse and admissible trajectory forecasting through multimodal context understanding
Seong Hyeon Park, Gyubok Lee, Manoj Bhat, Jimin Seo, Minseok Kang, Jonathan Francis, Ashwin R Jadhav, Paul Pu Liang, and Louis-Philippe Morency · 2020
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J. Betz, A. Wischnewski, A. Heilmeier, F. Nobis, T. Stahl, L. Hermansdorfer, and M. Lienkamp · 2019
Cited alongside, same era.
A survey of deep reinforcement learning in video games, 2019
K. Shao, Z. Tang, Y. Zhu, N. Li, and D. Zhao · 2019
Cited alongside, same era.
Multilayer graph-based trajectory planning for race vehicles in dynamic scenarios
T. Stahl, A. Wischnewski, J. Betz, and M. Lienkamp · 2019
Cited alongside, same era.
Deepracer: Autonomous racing platform for experimentation with sim2real reinforcement learning
B. Balaji, S. Mallya, S. Genc, S. Gupta, L. Dirac, V. Khare, G. Roy, T. Sun, Y. Tao, B. Townsend, E. Calleja, S. Muralidhara, and D. Karuppasamy · 2020
Cited alongside, same era.
Learning by cheating
Dian Chen, Brady Zhou, Vladlen Koltun, and Philipp Krähenbühl · 2020
Cited alongside, same era.
Can autonomous vehicles identify, recover from, and adapt to distribution shifts?
Angelos Filos, Panagiotis Tigas, Rowan McAllister, Nicholas Rhinehart, Sergey Levine, and Yarin Gal · 2020
Cited alongside, same era.
https://www.indyautonomouschallenge.com/
Indy autonomous challenge · 2021
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https://roborace.com/
Roborace · 2021
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http://torcs.sourceforge.net/index.php?name=Sections&op=viewarticle&artid=19
Torcs, the open racing car simulator · 2021
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Multimodal safety-critical scenarios generation for decision-making algorithms evaluation
Wenhao Ding, Baiming Chen, Bo Li, Kim Ji Eun, and Ding Zhao · 2021
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Maximum entropy rl (provably) solves some robust rl problems
Benjamin Eysenbach and Sergey Levine · 2021
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Core challenges in embodied vision-language planning
Jonathan Francis, Nariaki Kitamura, Felix Labelle, Xiaopeng Lu, Ingrid Navarro, and Jean Oh · 2021
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