331 citations · 565 across the 13 of their papers we have counts for
13 papers
Smoothing Policy Iteration for Zero-sum Markov Games
Yangang Ren, Yao Lyu, Wenxuan Wang +3
Zero-sum Markov Games (MGs) has been an efficient framework for multi-agent systems and robust control, wherein a minimax problem is constructed to solve the equilibrium policies.…
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…
Improve Generalization of Driving Policy at Signalized Intersections with Adversarial Learning
Yangang Ren, Guojian Zhan, Liye Tang +3
Intersections are quite challenging among various driving scenes wherein the interaction of signal lights and distinct traffic actors poses great difficulty to learn a wise and rob…
Self-learned Intelligence for Integrated Decision and Control of Automated Vehicles at Signalized Intersections
Yangang Ren, Jianhua Jiang, Dongjie Yu +4
Intersection is one of the most complex and accident-prone urban scenarios for autonomous driving wherein making safe and computationally efficient decisions is non-trivial. Curren…
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…
Integrated Decision and Control at Multi-Lane Intersections with Mixed Traffic Flow
Jianhua Jiang, Yangang Ren, Yang Guan +3
Autonomous driving at intersections is one of the most complicated and accident-prone traffic scenarios, especially with mixed traffic participants such as vehicles, bicycles and p…
Fixed-Dimensional and Permutation Invariant State Representation of Autonomous Driving
Jingliang Duan, Dongjie Yu, Shengbo Eben Li +4
In this paper, we propose a new state representation method, called encoding sum and concatenation (ESC), for the state representation of decision-making in autonomous driving. Unl…
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,…
Integrated Decision and Control: Towards Interpretable and Computationally Efficient Driving Intelligence
Yang Guan, Yangang Ren, Qi Sun +5
Decision and control are core functionalities of high-level automated vehicles. Current mainstream methods, such as functionality decomposition and end-to-end reinforcement learnin…
Improving Generalization of Reinforcement Learning with Minimax Distributional Soft Actor-Critic
Yangang Ren, Jingliang Duan, Shengbo Eben Li +2
Reinforcement learning (RL) has achieved remarkable performance in numerous sequential decision making and control tasks. However, a common problem is that learned nearly optimal p…
Distributional Soft Actor-Critic: Off-Policy Reinforcement Learning for Addressing Value Estimation Errors
Jingliang Duan, Yang Guan, Shengbo Eben Li +2
In reinforcement learning (RL), function approximation errors are known to easily lead to the Q-value overestimations, thus greatly reducing policy performance. This paper presents…
Direct and indirect reinforcement learning
Yang Guan, Shengbo Eben Li, Jingliang Duan +4
Reinforcement learning (RL) algorithms have been successfully applied to a range of challenging sequential decision making and control tasks. In this paper, we classify RL into dir…
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…