Solutions to estimation problems for scalar hamilton-jacobi equations using linear programming

Christian G. Claudel, Timothee Chamoin, Alexandre M. Bayen

Research output: Contribution to journalArticlepeer-review

7 Scopus citations

Abstract

This brief presents new convex formulations for solving estimation problems in systems modeled by scalar Hamilton-Jacobi (HJ) equations. Using a semi-analytic formula, we show that the constraints resulting from a HJ equation are convex, and can be written as a set of linear inequalities. We use this fact to pose various (and seemingly unrelated) estimation problems related to traffic flow-engineering as a set of linear programs. In particular, we solve data assimilation and data reconciliation problems for estimating the state of a system when the model and measurement constraints are incompatible. We also solve traffic estimation problems, such as travel time estimation or density estimation. For all these problems, a numerical implementation is performed using experimental data from the Mobile Century experiment. In the context of reproducible research, the code and data used to compute the results presented in this brief have been posted online and are accessible to regenerate the results. © 2013 IEEE.
Original languageEnglish (US)
Pages (from-to)273-280
Number of pages8
JournalIEEE Transactions on Control Systems Technology
Volume22
Issue number1
DOIs
StatePublished - Jan 2014

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Electrical and Electronic Engineering

Fingerprint

Dive into the research topics of 'Solutions to estimation problems for scalar hamilton-jacobi equations using linear programming'. Together they form a unique fingerprint.

Cite this