Section: New Results

Belief propagation inference for traffic prediction

Participants : Cyril Furtlehner, Jean-Marc Lasgouttes, Victorin Martin.

This work [55] 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. The main focus is on finding a good way to encode some coarse information (typically whether traffic on a segment is fluid or congested), and to decode it in the form of real-time traffic reconstruction and prediction. Our approach relies in particular on the belief propagation algorithm.

These studies have been done in particular in the framework of the projects Travesti and Pumas.

This year's highlights are

• Victorin Martin has defended his PhD thesis entitled “Modélisation probabiliste et inférence par l'algorithme Belief Propagation” [9] at Mines-ParisTech on May 23.

• The work about the theoretical aspects of encoding real valued variables into a binary Ising model has been published as a research report [44] and submitted for publication.