TRAVESTI stands for “TRAffic Volume Estimation by Spatio-Temporal Inference.”
ANR SYSCOMM Project N°ANR-08-SYSC-017
This project addresses the problem of modelling large scale complex systems to provide predictions of their macroscopic behaviour. For application purpose, we focus here on the particular problem of the real-time prediction of traffic conditions on a road network.
Car traffic is a typical complex system which exhibits emerging phenomena such as jam formation and long distance interactions throughout a network. In particular we focus on the analysis of the traffic patterns delivered by the METROPOLIS traffic simulation software, in order to set up a prediction method based on a statistical physics modelling and message-passing algorithms.
We plan to study two types of traffic conditions:
As usual for complex systems, the issue is to extract from local interaction rules, a macroscopic representation of the behaviour of the system. By definition of a complex system, it exhibits macroscopic phenomena that cannot be directly deduced from individual microscopic behaviours and the understanding of the overall behaviour of the system resides in the identification of relevant variables and macroscopic structures.
In the target application, we consider two complementary points of view:
Our proposal focuses on developing a new approach to this second point of view with large scale and real time constraints. The tools which will be used are
To produce the data, METROPOLIS will be our basic tool, serving either as a proxy for real world data or for creating synthetic conditions.