Networked traffic state estimation involving mixed fixed-mobile sensor data using Hamilton-Jacobi equations

Edward S. Canepa, Christian G. Claudel

    Research output: Contribution to journalArticlepeer-review

    13 Scopus citations

    Abstract

    Nowadays, traffic management has become a challenge for urban areas, which are covering larger geographic spaces and facing the generation of different kinds of traffic data. This article presents a robust traffic estimation framework for highways modeled by a system of Lighthill Whitham Richards equations that is able to assimilate different sensor data available. We first present an equivalent formulation of the problem using a Hamilton–Jacobi equation. Then, using a semi-analytic formula, we show that the model constraints resulting from the Hamilton–Jacobi equation are linear ones. We then pose the problem of estimating the traffic density given incomplete and inaccurate traffic data as a Mixed Integer Program. We then extend the density estimation framework to highway networks with any available data constraint and modeling junctions. Finally, we present a travel estimation application for a small network using real traffic measurements obtained obtained during Mobile Century traffic experiment, and comparing the results with ground truth data.
    Original languageEnglish (US)
    Pages (from-to)686-709
    Number of pages24
    JournalTransportation Research Part B: Methodological
    Volume104
    DOIs
    StatePublished - Jun 19 2017

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