70 citations · 142 across the 16 of their papers we have counts for
4 papers · 1 filter
Identify, Estimate and Bound the Uncertainty of Reinforcement Learning for Autonomous Driving
Weitao Zhou, Zhong Cao, Nanshan Deng +2
Deep reinforcement learning (DRL) has emerged as a promising approach for developing more intelligent autonomous vehicles (AVs). A typical DRL application on AVs is to train a neur…
Privacy of Autonomous Vehicles: Risks, Protection Methods, and Future Directions
Chulin Xie, Zhong Cao, Yunhui Long +3
Recent advances in machine learning have enabled its wide application in different domains, and one of the most exciting applications is autonomous vehicles (AVs), which have encou…
Long-Tail Prediction Uncertainty Aware Trajectory Planning for Self-driving Vehicles
Weitao Zhou, Zhong Cao, Yunkang Xu +4
A typical trajectory planner of autonomous driving commonly relies on predicting the future behavior of surrounding obstacles. Recently, deep learning technology has been widely ad…
Hybrid Car-Following Strategy based on Deep Deterministic Policy Gradient and Cooperative Adaptive Cruise Control
Ruidong Yan, Rui Jiang, Bin Jia +2
Deep deterministic policy gradient (DDPG)-based car-following strategy can break through the constraints of the differential equation model due to the ability of exploration on com…