72 citations · 161 across the 14 of their papers we have counts for
8 papers · 1 filter
Quadratic Q-network for Learning Continuous Control for Autonomous Vehicles
Pin Wang, Hanhan Li, Ching-Yao Chan
Reinforcement Learning algorithms have recently been proposed to learn time-sequential control policies in the field of autonomous driving. Direct applications of Reinforcement Lea…
Decision Making for Autonomous Driving via Augmented Adversarial Inverse Reinforcement Learning
Pin Wang, Dapeng Liu, Jiayu Chen +2
Making decisions in complex driving environments is a challenging task for autonomous agents. Imitation learning methods have great potentials for achieving such a goal. Adversaria…
Intention-aware Long Horizon Trajectory Prediction of Surrounding Vehicles using Dual LSTM Networks
Long Xin, Pin Wang, Ching-Yao Chan +3
As autonomous vehicles (AVs) need to interact with other road users, it is of importance to comprehensively understand the dynamic traffic environment, especially the future possib…
A Data Driven Method of Feedforward Compensator Optimization for Autonomous Vehicle Control
Pin Wang, Tianyu Shi, Chonghao Zou +2
A reliable controller is critical for execution of safe and smooth maneuvers of an autonomous vehicle. The controller must be robust to external disturbances, such as road surface,…
Continuous Control for Automated Lane Change Behavior Based on Deep Deterministic Policy Gradient Algorithm
Pin Wang, Hanhan Li, Ching-Yao Chan
Lane change is a challenging task which requires delicate actions to ensure safety and comfort. Some recent studies have attempted to solve the lane-change control problem with Rei…
A Reinforcement Learning Approach for Intelligent Traffic Signal Control at Urban Intersections
Mengyu Guo, Pin Wang, Ching-Yao Chan +1
Ineffective and inflexible traffic signal control at urban intersections can often lead to bottlenecks in traffic flows and cause congestion, delay, and environmental problems. How…
Driving Decision and Control for Autonomous Lane Change based on Deep Reinforcement Learning
Tianyu Shi, Pin Wang, Xuxin Cheng +2
We apply Deep Q-network (DQN) with the consideration of safety during the task for deciding whether to conduct the maneuver. Furthermore, we design two similar Deep Q learning fram…
A Data Driven Method of Optimizing Feedforward Compensator for Autonomous Vehicle
Tianyu Shi, Pin Wang, Ching-Yao Chan +1
A reliable controller is critical and essential for the execution of safe and smooth maneuvers of an autonomous vehicle.The controller must be robust to external disturbances, such…