124 citations · 182 across the 4 of their papers we have counts for
4 papers
Discovering State Variables Hidden in Experimental Data
Boyuan Chen, Kuang Huang, Sunand Raghupathi +3
All physical laws are described as relationships between state variables that give a complete and non-redundant description of the relevant system dynamics. However, despite the pr…
A Physics-Informed Deep Learning Paradigm for Traffic State and Fundamental Diagram Estimation
Rongye Shi, Zhaobin Mo, Kuang Huang +2
Traffic state estimation (TSE) bifurcates into two categories, model-driven and data-driven (e.g., machine learning, ML), while each suffers from either deficient physics or small…
Physics-Informed Deep Learning for Traffic State Estimation
Rongye Shi, Zhaobin Mo, Kuang Huang +2
Traffic state estimation (TSE), which reconstructs the traffic variables (e.g., density) on road segments using partially observed data, plays an important role on efficient traffi…
Dynamic driving and routing games for autonomous vehicles on networks: A mean field game approach
Kuang Huang, Xu Chen, Xuan Di +1
This paper aims to answer the research question as to optimal design of decision-making processes for autonomous vehicles (AVs), including dynamical selection of driving velocity a…