Compression, estimation and prediction models for large road networks

Abstract

Developing models for large road networks is not a trivial task. We propose data driven models that can help intelligent transportation systems (ITS) in dealing with issues such as managing large amount of traffic information and incomplete data sets. Furthermore, we also discuss the problem of traffic prediction in the context of large-scale networks.