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An Ising Model for Road Traffic Inference

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Book cover From Hamiltonian Chaos to Complex Systems

Part of the book series: Nonlinear Systems and Complexity ((NSCH,volume 5))

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Abstract

We review some properties of the “belief propagation” algorithm, a distributed iterative map used to perform Bayesian inference and present some recent work where this algorithm serves as a starting point to encode observation data into a probabilistic model and to process large-scale information in real time. A natural approach is based on the linear response theory and various recent instantiations are presented. We will focus on the particular situation where the data have many different statistical components, representing a variety of independent patterns. As an application, the problem of reconstructing and predicting traffic states based on floating car data is then discussed.

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Notes

  1. 1.

    Potentially any arbitrary mapping ϕ(x) could be considered to perform the moment matching.

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Acknowledgment

This gives me the occasion to express my warm thanks to my colleagues Victorin Martin and Jean-Marc Lasgouttes with whom it is a pleasure to collaborate on the main subjects discussed in this review. I am also grateful to Anne Auger, Yufei Han, Fabrice Marchal and Fabien Moutarde, for many aspects mentioned in this work concerning ongoing projects. This work was supported by the grant ANR-08-SYSC-017 from the French National Research Agency.

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Authors and Affiliations

  1. INRIA Saclay – LRI, Bat. 490, Université Paris-Sud, Orsay, 91405, France

    Cyril Furtlehner

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  1. Cyril Furtlehner
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Correspondence to Cyril Furtlehner .

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Editors and Affiliations

  1. , Centre de Physique Théorique, Aix-Marseille Université, Luminy Case 907, Marseille Cedex 09, 13288, France

    Xavier Leoncini

  2. Scientifique, Institut de Recherche sur le Phénomènes, Centre National de la Recherche, rue F. Joliot-Curie 49, Marseille Cedex 13, 13384, France

    Marc Leonetti

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Furtlehner, C. (2013). An Ising Model for Road Traffic Inference. In: Leoncini, X., Leonetti, M. (eds) From Hamiltonian Chaos to Complex Systems. Nonlinear Systems and Complexity, vol 5. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-6962-9_10

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  • DOI: https://doi.org/10.1007/978-1-4614-6962-9_10

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