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We investigate methods to provide safety assurances for autonomous agents that incorporate predictions of other, uncontrolled agents' behavior into their own trajectory planning.
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Roger Koenker · 2005
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“Hamilton-jacobi reachability: A brief overview and recent advances”
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“Neural network-based uncertainty quantification: A survey of methodologies and applications”
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“Conformal prediction under covariate shift”
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“Trajectron++: Dynamically-feasible trajectory forecasting with heterogeneous data”
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“Confidence-aware motion prediction for real-time collision avoidance”
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“Disentangling epistemic and aleatoric uncertainty in reinforcement learning”
Bertrand Charpentier, Ransalu Senanayake, Mykel Kochenderfer and Stephan Gunnemann · 2022
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“Sample-efficient safety assurances using conformal prediction”
Rachel Luo et al · 2022
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“Adaptive Conformal Prediction for Motion Planning among Dynamic Agents”
Anushri Dixit, Lars Lindemann, Skylar Wei, Matthew Cleaveland, George Pappas and Joel Burdick · 2022
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“Conformal prediction beyond exchangeability”
Rina Barber, Emmanuel Candes, Aaditya Ramdas and Ryan Tibshirani · 2022
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“Online update of safety assurances using confidence-based predictions”
Kensuke Nakamura and Somil Bansal · 2022
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“Nocturne: a scalable driving benchmark for bringing multi-agent learning one step closer to the real world”
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Chen Xu and Yao Xie · 2021
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Isaac Gibbs and Emmanuel Candes · 2021
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“Data-driven reachability analysis with Christoffel functions”
Alex Devonport, Forest Yang, Laurent El and Murat Arcak · 2021
Cited alongside, same era.
“hj_reachability”
Edward Schmerling · 2021
Cited alongside, same era.
“Large Scale Interactive Motion Forecasting for Autonomous Driving: The Waymo Open Motion Dataset”
Scott Ettinger et al · 2021
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“Multipath++: Efficient information fusion and trajectory aggregation for behavior prediction”
Balakrishnan Varadarajan et al · 2022
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Eugene Vinitsky, Nathan Lichtl“’e, Xiaomeng Yang, Brandon Amos and Jakob Foerster · 2022
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Anish Muthali et al · 2023
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Renukanandan Tumu, Lars Lindemann, Truong Nghiem and Rahul Mangharam · 2023
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Lars Lindemann, Matthew Cleaveland, Gihyun Shim and George Pappas · 2023
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“Achieving Risk Control in Online Learning Settings”
Shai Feldman, Liran Ringel, Stephen Bates and Yaniv Romano · 2023
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