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20192022
most citedFeasible Actor-Critic: Constrained Reinforcement Learning for Ensuring Statewise Safety

19 citations · 36 across the 12 of their papers we have counts for

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5 papers · 1 filter

cs.RO20221 cited

Integrated Decision and Control for High-Level Automated Vehicles by Mixed Policy Gradient and Its Experiment Verification

Yang Guan, Liye Tang, Chuanxiao Li +5

Self-evolution is indispensable to realize full autonomous driving. This paper presents a self-evolving decision-making system based on the Integrated Decision and Control (IDC), a…

cs.RO20215 cited

Encoding Distributional Soft Actor-Critic for Autonomous Driving in Multi-lane Scenarios

Jingliang Duan, Yangang Ren, Fawang Zhang +5

In this paper, we propose a new reinforcement learning (RL) algorithm, called encoding distributional soft actor-critic (E-DSAC), for decision-making in autonomous driving. Unlike…

cs.RO20212 cited

Decision-Making under On-Ramp merge Scenarios by Distributional Soft Actor-Critic Algorithm

Yiting Kong, Yang Guan, Jingliang Duan +3

Merging into the highway from the on-ramp is an essential scenario for automated driving. The decision-making under the scenario needs to balance the safety and efficiency performa…

cs.RO20218 cited

Model-based Constrained Reinforcement Learning using Generalized Control Barrier Function

Haitong Ma, Jianyu Chen, Shengbo Eben Li +4

Model information can be used to predict future trajectories, so it has huge potential to avoid dangerous region when implementing reinforcement learning (RL) on real-world tasks,…

cs.RO2019

Centralized Cooperation for Connected and Automated Vehicles at Intersections by Proximal Policy Optimization

Yang Guan, Yangang Ren, Shengbo Eben Li +3

Connected vehicles will change the modes of future transportation management and organization, especially at an intersection without traffic light. Centralized coordination methods…