Skip to Main content Skip to Navigation
New interface
Conference papers

A Belief Propagation Approach to Traffic Prediction using Probe Vehicles

Cyril Furtlehner 1 Jean-Marc Lasgouttes 2 Arnaud de La Fortelle 2, 3 
1 TANC - Algorithmic number theory for cryptology
LIX - Laboratoire d'informatique de l'École polytechnique [Palaiseau], Inria Saclay - Ile de France
Abstract : This paper deals with real-time prediction of traffic conditions in a setting where the only available information is floating car data (FCD) sent by probe vehicles. Starting from the Ising model of statistical physics, we use a discretized space-time traffic description, on which we define and study an inference method based on the Belief Propagation (BP) algorithm. The idea is to encode into a graph the \emph{a priori} information derived from historical data (marginal probabilities of pairs of variables), and to use BP to estimate the actual state from the latest FCD. The behavior of the algorithm is illustrated by numerical studies on a simple simulated traffic network. The generalization to the superposition of many traffic patterns is discussed.
Complete list of metadata

Cited literature [18 references]  Display  Hide  Download
Contributor : Cyril Furtlehner Connect in order to contact the contributor
Submitted on : Friday, September 28, 2007 - 7:01:28 PM
Last modification on : Tuesday, October 25, 2022 - 4:23:34 PM
Long-term archiving on: : Friday, April 9, 2010 - 3:08:19 AM


Files produced by the author(s)


  • HAL Id : hal-00175627, version 1


Cyril Furtlehner, Jean-Marc Lasgouttes, Arnaud de La Fortelle. A Belief Propagation Approach to Traffic Prediction using Probe Vehicles. 10th International IEEE Conference on Intelligent Transportation Systems, Sep 2007, Seattle, United States. pp. 1022-1027. ⟨hal-00175627⟩



Record views


Files downloads