OD MATRICES ESTIMATION FROM LINK FLOWS BY NEURAL NETWORKS AND PCA

The paper tackles OD matrix estimation starting from the measures of flow on road network links and proposes the application of soft-computing techniques. The application scenarios are two: a trial network and the real rural network of the Province of Naples both simulated by a micro-simulator dynamically assigning known OD matrices. A PCA (Principal Component Analysis) technique was also used to reduce the input space of variables in order to achieve better significance for input data and to study the possible eigengraphs of the road networks.