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11/22/2022
Safe Control and Learning Using Generalized Action Governor
This paper introduces the Generalized Action Governor, which is a superv...
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11/22/2022
REFINE: Reachability-based Trajectory Design using Robust Feedback Linearization and Zonotopes
Performing real-time receding horizon motion planning for autonomous veh...
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07/17/2022
Robust Action Governor for Uncertain Piecewise Affine Systems with Non-convex Constraints and Safe Reinforcement Learning
The action governor is an add-on scheme to a nominal control loop that m...
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12/14/2021
Interaction-Aware Trajectory Prediction and Planning for Autonomous Vehicles in Forced Merge Scenarios
Merging is, in general, a challenging task for both human drivers and au...
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09/20/2021
Stochastic MPC with Multi-modal Predictions for Traffic Intersections
We propose a Stochastic MPC (SMPC) formulation for autonomous driving at...
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08/19/2021
Prior Is All You Need to Improve the Robustness and Safety for the First Time Deployment of Meta RL
The field of Meta Reinforcement Learning (Meta-RL) has seen substantial ...
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04/18/2021
Quick Learner Automated Vehicle Adapting its Roadmanship to Varying Traffic Cultures with Meta Reinforcement Learning
It is essential for an automated vehicle in the field to perform discret...
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02/21/2021
Safe Reinforcement Learning Using Robust Action Governor
Reinforcement Learning (RL) is essentially a trial-and-error learning pr...
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05/11/2020
A Game Theoretic Approach for Parking Spot Search with Limited Parking Lot Information
We propose a game theoretic approach to address the problem of searching...
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03/18/2020
Generating Socially Acceptable Perturbations for Efficient Evaluation of Autonomous Vehicles
Deep reinforcement learning methods have been widely used in recent year...
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10/28/2019
Deep Reinforcement Learning with Enhanced Safety for Autonomous Highway Driving
In this paper, we present a safe deep reinforcement learning system for ...
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04/03/2019
