activity
20172022
most citedIdentifying trending coefficients with an ensemble Kalman filter

1 citations · 2 across the 4 of their papers we have counts for

collaborators

11 papers

math.NA2022

Recent Trends on Nonlinear Filtering for Inverse Problems

Michael Herty, Elisa Iacomini, Giuseppe Visconti

Among the class of nonlinear particle filtering methods, the Ensemble Kalman Filter (EnKF) has gained recent attention for its use in solving inverse problems. We review the origin…

physics.soc-ph20211 cited

Model of vehicle interactions with autonomous cars and its properties

M. Herty, G. Puppo, G. Visconti

We study a hierarchy of models based on kinetic equations for the descriptions of traffic flow in presence of autonomous and human--driven vehicles. The autonomous cars considered…

math.AP2020

From kinetic to macroscopic models and back

M. Herty, G. Puppo, G. Visconti

We study kinetic models for traffic flow characterized by the property of producing backward propagating waves. These waves may be identified with the phenomenon of stop-and-go wav…

math.OC20201 cited

Identifying trending coefficients with an ensemble Kalman filter

M. Schwenzer, G. Visconti, M. Ay +3

This paper extends the ensemble Kalman filter (EnKF) for inverse problems to identify trending model coefficients. This is done by repeatedly inflating the ensemble while maintaini…

nlin.AO2019

Reconstruction of traffic speed distributions from kinetic models with uncertainties

M. Herty, A. Tosin, G. Visconti +1

In this work we investigate the ability of a kinetic approach for traffic dynamics to predict speed distributions obtained through rough data. The present approach adopts the forma…

math.NA2019

Continuous Limits for Constrained Ensemble Kalman Filter

Michael Herty, Giuseppe Visconti

The Ensemble Kalman Filter method can be used as an iterative particle numerical scheme for state dynamics estimation and control--to--observable identification problems. In applic…