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Road trafficking description and short term travel time forecasting, with a classification method
Author(s) -
Loubesi JeanMichel,
Maza Élie,
Lavielle Marc,
Rodriguez Luis
Publication year - 2006
Publication title -
canadian journal of statistics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.804
H-Index - 51
eISSN - 1708-945X
pISSN - 0319-5724
DOI - 10.1002/cjs.5550340307
Subject(s) - term (time) , computer science , work (physics) , road traffic , travel time , transport engineering , engineering , mechanical engineering , physics , quantum mechanics
The purpose of this work is, on the one hand, to study how to forecast road trafficking on highway networks and, on the other hand, to describe future traffic events. Here, road trafficking is measured by vehicle velocities. The authors propose two methodologies. The first is based on an empirical classification method, and the second on a probability mixture model. They use an SAEM‐type algorithm (a stochastic approximation of the EM algorithm) to select the densities of the mixture model. Then, they test the validity of their methodologies by forecasting short term travel times.