2 citations · 9 across the 9 of their papers we have counts for
9 papers
Dream to Adapt: Meta Reinforcement Learning by Latent Context Imagination and MDP Imagination
Lu Wen, Songan Zhang, H. Eric Tseng +1
Meta reinforcement learning (Meta RL) has been amply explored to quickly learn an unseen task by transferring previously learned knowledge from similar tasks. However, most state-o…
A Hybrid Partitioning Strategy for Backward Reachability of Neural Feedback Loops
Nicholas Rober, Michael Everett, Songan Zhang +1
As neural networks become more integrated into the systems that we depend on for transportation, medicine, and security, it becomes increasingly important that we develop methods t…
Improved Robustness and Safety for Pre-Adaptation of Meta Reinforcement Learning with Prior Regularization
Lu Wen, Songan Zhang, H. Eric Tseng +3
Meta Reinforcement Learning (Meta-RL) has seen substantial advancements recently. In particular, off-policy methods were developed to improve the data efficiency of Meta-RL techniq…
Quick Learner Automated Vehicle Adapting its Roadmanship to Varying Traffic Cultures with Meta Reinforcement Learning
Songan Zhang, Lu Wen, Huei Peng +1
It is essential for an automated vehicle in the field to perform discretionary lane changes with appropriate roadmanship - driving safely and efficiently without annoying or endang…
Monocular 3D Vehicle Detection Using Uncalibrated Traffic Cameras through Homography
Minghan Zhu, Songan Zhang, Yuanxin Zhong +3
This paper proposes a method to extract the position and pose of vehicles in the 3D world from a single traffic camera. Most previous monocular 3D vehicle detection algorithms focu…
An Interaction-aware Evaluation Method for Highly Automated Vehicles
Xinpeng Wang, Songan Zhang, Kuan-Hui Lee +1
It is important to build a rigorous verification and validation (V&V) process to evaluate the safety of highly automated vehicles (HAVs) before their wide deployment on public road…
Driving-Policy Adaptive Safeguard for Autonomous Vehicles Using Reinforcement Learning
Zhong Cao, Shaobing Xu, Songan Zhang +2
Safeguard functions such as those provided by advanced emergency braking (AEB) can provide another layer of safety for autonomous vehicles (AV). A smart safeguard function should a…
Generating Socially Acceptable Perturbations for Efficient Evaluation of Autonomous Vehicles
Songan Zhang, Huei Peng, Subramanya Nageshrao +1
Deep reinforcement learning methods have been widely used in recent years for autonomous vehicle's decision-making. A key issue is that deep neural networks can be fragile to adver…
Developing Robot Driver Etiquette Based on Naturalistic Human Driving Behavior
Xianan Huang, Songan Zhang, Huei Peng
Automated vehicles can change the society by improved safety, mobility and fuel efficiency. However, due to the higher cost and change in business model, over the coming decades, t…