Dynamic density and flow reconstruction in large-scale urban networks using heterogeneous data sources

Abstract

This work proposes an estimator for the vehicle density of every road section of a large urban traffic network using a data-based approach. We assume that a limited number of flow and turning ratio sensors can be installed and that aggregate Floating Car Data are available. To validate the estimator, real data obtained in the city of Grenoble in France is used. The results show that the trajectories of the real and estimated flows and density are very close, showing the good performance of the proposed methods.