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Uncertainty on human behaviors poses a significant challenge to autonomous driving in crowded urban environments.
Acting optimally in partially observable stochastic domains
A. R. Cassandra, L. P. Kaelbling, and M. L. Littman · 1994
Earlier work this paper cites.
Planning and acting in partially observable stochastic domains
L. P. Kaelbling, M. L. Littman, and A. R. Cassandra · 1998
Earlier work this paper cites.
Monte-carlo planning in large pomdps
D. Silver and J. Veness · 2010
Earlier work this paper cites.
Despot: Online pomdp planning with regularization
A. Somani, N. Ye, D. Hsu, and W. S. Lee · 2013
Earlier work this paper cites.
Auto-encoding variational bayes
D. P. Kingma and M. Welling · 2013
Earlier work this paper cites.
Continuous real time pomcp to find-and-follow people by a humanoid service robot
A. Goldhoorn, A. Garrell, R. Alquézar, and A. Sanfeliu · 2014
Earlier work this paper cites.
Empirical evaluation of gated recurrent neural networks on sequence modeling
J. Chung, C. Gulcehre, K. Cho, and Y. Bengio · 2014
Earlier work this paper cites.
Act to see and see to act: Pomdp planning for objects search in clutter
J. K. Li, D. Hsu, and W. S. Lee · 2016
Earlier work this paper cites.
Evaluating trajectory collision probability through adaptive importance sampling for safe motion planning
E. Schmerling and M. Pavone · 2017
Earlier work this paper cites.
Safe model-based reinforcement learning with stability guarantees
F. Berkenkamp, M. Turchetta, A. Schoellig, and A. Krause · 2017
Earlier work this paper cites.
Autonomous cars: Research results, issues, and future challenges
R. Hussain and S. Zeadally · 2018
Earlier work this paper cites.
Scalable end-to-end autonomous vehicle testing via rare-event simulation
M. O’Kelly, A. Sinha, H. Namkoong, R. Tedrake, and J. C. Duchi · 2018
Earlier work this paper cites.
Hybrid risk-aware conditional planning with applications in autonomous vehicles
X. Huang, A. Jasour, M. Deyo, A. Hofmann, and B. C. Williams · 2018
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High-level decision making for safe and reasonable autonomous lane changing using reinforcement learning
B. Mirchevska, C. Pek, M. Werling, M. Althoff, and J. Boedecker · 2018
Cited alongside, same era.
Leave no trace: Learning to reset for safe and autonomous reinforcement learning
B. Eysenbach, S. Gu, J. Ibarz, and S. Levine · 2018
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Online planning for target object search in clutter under partial observability
Y. Xiao, S. Katt, A. ten Pas, S. Chen, and C. Amato · 2019
Cited alongside, same era.
Importance sampling for online planning under uncertainty
Y. Luo, H. Bai, D. Hsu, and W. S. Lee · 2019
Cited alongside, same era.
A behavior driven approach for sampling rare event situations for autonomous vehicles
Hyp-despot: A hybrid parallel algorithm for online planning under uncertainty
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Later among the works it cites.
Deep probabilistic accelerated evaluation: A robust certifiable rare-event simulation methodology for black-box safety-critical systems
M. Arief, Z. Huang, G. K. S. Kumar, Y. Bai, S. He, W. Ding, H. Lam, and D. Zhao · 2021
Later among the works it cites.
Re-understanding finite-state representations of recurrent policy networks
M. H. Danesh, A. Koul, A. Fern, and S. Khorram · 2021
Later among the works it cites.
Risk-aware motion planning for autonomous vehicles with safety specifications
T. Nyberg, C. Pek, L. Dal Col, C. Norén, and J. Tumova · 2021
Later among the works it cites.
Safe reinforcement learning by imagining the near future
G. Thomas, Y. Luo, and T. Ma · 2021
Later among the works it cites.
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Bi-directional value learning for risk-aware planning under uncertainty
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LeTS-Drive: Driving in a crowd by learning from tree search
P. Cai, Y. Luo, A. Saxena, D. Hsu, and W. S. Lee · 2019
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Risk-aware high-level decisions for automated driving at occluded intersections with reinforcement learning
D. Kamran, C. F. Lopez, M. Lauer, and C. Stiller · 2020
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SUMMIT: A simulator for urban driving in massive mixed traffic
P. Cai, Y. Lee, Y. Luo, and D. Hsu · 2020
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Scalability in perception for autonomous driving: Waymo open dataset
P. Sun, H. Kretzschmar, X. Dotiwalla, A. Chouard, V. Patnaik, P. Tsui, J. Guo, Y. Zhou, Y. Chai, B. Caine, et al · 2020
Cited alongside, same era.
M. H. Danesh and A. Fern · 2021
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MAGIC: Learning macro-actions for online pomdp planning
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Later among the works it cites.
Argoverse 2: Next generation datasets for self-driving perception and forecasting
B. Wilson, W. Qi, T. Agarwal, J. Lambert, J. Singh, S. Khandelwal, B. Pan, R. Kumar, A. Hartnett, J. Kaesemodel Pontes, D. Ramanan, P. Carr, and J. Hays · 2021
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Looking for trouble: Informative planning for safe trajectories with occlusions
B. Gilhuly, A. Sadeghi, P. Yedmellat, K. Rezaee, and S. L. Smith · 2022
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Closing the planning-learning loop with application to autonomous driving in a crowd
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Gamma: A general agent motion model for autonomous driving
Y. Luo, P. Cai, Y. Lee, and D. Hsu · 2022
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