5 citations · 5 across the 1 of their papers we have counts for
5 papers
Autonomous Driving using Safe Reinforcement Learning by Incorporating a Regret-based Human Lane-Changing Decision Model
Dong Chen, Longsheng Jiang, Yue Wang +1
It is expected that many human drivers will still prefer to drive themselves even if the self-driving technologies are ready. Therefore, human-driven vehicles and autonomous vehicl…
Respect Your Emotion: Human-Multi-Robot Teaming based on Regret Decision Model
Longsheng Jiang, Yue Wang
Often, when modeling human decision-making behaviors in the context of human-robot teaming, the emotion aspect of human is ignored. Nevertheless, the influence of emotion, in some…
Human-Robot Trust Integrated Task Allocation and Symbolic Motion planning for Heterogeneous Multi-robot Systems
Huanfei Zheng, Zhanrui Liao, Yue Wang
This paper presents a human-robot trust integrated task allocation and motion planning framework for multi-robot systems (MRS) in performing a set of tasks concurrently. A set of t…
A Human-Computer Interface Design for Quantitative Measure of Regret Theory
Longsheng Jiang, Yue Wang
Regret theory is a theory that describes human decision-making under risk. The key of obtaining a quantitative model of regret theory is to measure the preference in humans' mind w…
Trust-based Multi-Robot Symbolic Motion Planning with a Human-in-the-Loop
Yue Wang, Laura R. Humphrey, Zhanrui Liao +1
Symbolic motion planning for robots is the process of specifying and planning robot tasks in a discrete space, then carrying them out in a continuous space in a manner that preserv…