52 citations · 107 across the 7 of their papers we have counts for
4 papers · 1 filter
Fourier neural operator for learning solutions to macroscopic traffic flow models: Application to the forward and inverse problems
Bilal Thonnam Thodi, Sai Venkata Ramana Ambadipudi, Saif Eddin Jabari
Deep learning methods are emerging as popular computational tools for solving forward and inverse problems in traffic flow. In this paper, we study a neural operator framework for…
Learning-based solutions to nonlinear hyperbolic PDEs: Empirical insights on generalization errors
Bilal Thonnam Thodi, Sai Venkata Ramana Ambadipudi, Saif Eddin Jabari
We study learning weak solutions to nonlinear hyperbolic partial differential equations (H-PDE), which have been difficult to learn due to discontinuities in their solutions. We us…
Learning Traffic Speed Dynamics from Visualizations
Bilal Thonnam Thodi, Zaid Saeed Khan, Saif Eddin Jabari +1
Space-time visualizations of macroscopic or microscopic traffic variables is a qualitative tool used by traffic engineers to understand and analyze different aspects of road traffi…
Incorporating Kinematic Wave Theory into a Deep Learning Method for High-Resolution Traffic Speed Estimation
Bilal Thonnam Thodi, Zaid Saeed Khan, Saif Eddin Jabari +1
We propose a kinematic wave-based Deep Convolutional Neural Network (Deep CNN) to estimate high-resolution traffic speed fields from sparse probe vehicle trajectories. We introduce…