72 citations · 161 across the 14 of their papers we have counts for
15 papers
A Survey of Deep Reinforcement Learning Algorithms for Motion Planning and Control of Autonomous Vehicles
Fei Ye, Shen Zhang, Pin Wang +1
In this survey, we systematically summarize the current literature on studies that apply reinforcement learning (RL) to the motion planning and control of autonomous vehicles. Many…
Meta-Adversarial Inverse Reinforcement Learning for Decision-making Tasks
Pin Wang, Hanhan Li, Ching-Yao Chan
Learning from demonstrations has made great progress over the past few years. However, it is generally data hungry and task specific. In other words, it requires a large amount of…
Meta Reinforcement Learning-Based Lane Change Strategy for Autonomous Vehicles
Fei Ye, Pin Wang, Ching-Yao Chan +1
Recent advances in supervised learning and reinforcement learning have provided new opportunities to apply related methodologies to automated driving. However, there are still chal…
Automated Lane Change Strategy using Proximal Policy Optimization-based Deep Reinforcement Learning
Fei Ye, Xuxin Cheng, Pin Wang +2
Lane-change maneuvers are commonly executed by drivers to follow a certain routing plan, overtake a slower vehicle, adapt to a merging lane ahead, etc. However, improper lane chang…
TPPO: A Novel Trajectory Predictor with Pseudo Oracle
Biao Yang, Caizhen He, Pin Wang +3
Forecasting pedestrian trajectories in dynamic scenes remains a critical problem in various applications, such as autonomous driving and socially aware robots. Such forecasting is…
A Novel Graph based Trajectory Predictor with Pseudo Oracle
Biao Yang, Guocheng Yan, Pin Wang +3
Pedestrian trajectory prediction in dynamic scenes remains a challenging and critical problem in numerous applications, such as self-driving cars and socially aware robots. Challen…