14 citations · 30 across the 9 of their papers we have counts for
9 papers
An Explicit Discrete-Time Dynamic Vehicle Model with Assured Numerical Stability
Guojian Zhan, Qiang Ge, Haoyu Gao +3
Numerical stability is of great significance for discrete-time dynamic vehicle model. Among the unstable factors, low-speed singularity stands out as one of the most challenging is…
Quantitative Representation of Scenario Difficulty for Autonomous Driving Based on Adversarial Policy Search
Shuo Yang, Caojun Wang, Yuanjian Zhang +4
Adversarial scenario generation is crucial for autonomous driving testing because it can efficiently simulate various challenge and complex traffic conditions. However, it is diffi…
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…
Approximate Optimal Filter for Linear Gaussian Time-invariant Systems
Kaiming Tang, Shengbo Eben Li, Yuming Yin +4
State estimation is critical to control systems, especially when the states cannot be directly measured. This paper presents an approximate optimal filter, which enables to use pol…
Recurrent Model Predictive Control
Zhengyu Liu, Jingliang Duan, Wenxuan Wang +5
This paper proposes an off-line algorithm, called Recurrent Model Predictive Control (RMPC), to solve general nonlinear finite-horizon optimal control problems. Unlike traditional…
Recurrent Model Predictive Control: Learning an Explicit Recurrent Controller for Nonlinear Systems
Zhengyu Liu, Jingliang Duan, Wenxuan Wang +4
This paper proposes an offline control algorithm, called Recurrent Model Predictive Control (RMPC), to solve large-scale nonlinear finite-horizon optimal control problems. It can b…
Model-Based Actor-Critic with Chance Constraint for Stochastic System
Baiyu Peng, Yao Mu, Yang Guan +3
Safety is essential for reinforcement learning (RL) applied in real-world situations. Chance constraints are suitable to represent the safety requirements in stochastic systems. Pr…
Ternary Policy Iteration Algorithm for Nonlinear Robust Control
Jie Li, Shengbo Eben Li, Yang Guan +3
The uncertainties in plant dynamics remain a challenge for nonlinear control problems. This paper develops a ternary policy iteration (TPI) algorithm for solving nonlinear robust c…
Continuous-time finite-horizon ADP for automated vehicle controller design with high efficiency
Ziyu Lin, Jingliang Duan, Shengbo Eben Li +2
The design of an automated vehicle controller can be generally formulated into an optimal control problem. This paper proposes a continuous-time finite-horizon approximate dynamicp…