Intelligent transportation systems have enormous potential for improving the quality of our
lives. They rely on traffic monitoring and control infrastructures to enable an efficient …

Traffic control is essential for the achievement of a sustainable and safe mobility. Monitoring
systems deployed over the roads collect a great amount of traffic data that must be efficiently …

Traffic conditions can be more accurately estimated using data assimilation techniques
since these methods incorporate an imperfect traffic simulation model with the (partial) noisy …

The problem of modeling and predicting spatiotemporal traffic phenomena over an urban
road network is important to many traffic applications such as detecting and forecasting …

This paper formulates a consensus filter-based distributed variational Bayesian (CFBDVB)
algorithm for density approximation of traffic flow and average traffic speed in a freeway. This …

This paper addresses the problem of density reconstruction in traffic networks with
heterogeneous information sources. The network is partitioned in cells in which vehicles …

This PhD thesis is done in the context of the ERC Advanced Grant project Scale-FreeBack.
Its overall aim is to set new foundations for a theory dealing with complex physical networks …

Nowadays, traffic management has become a challenge for urban areas, which are covering
larger geographic spaces and facing the generation of different kinds of traffic data. This …

In this paper we consider a network of agents monitoring a spatially distributed traffic
process. Each node measures the number of arrivals seen at its monitoring point in a given …

Network traffic prediction based on probe vehicle data is important for traffic management
and route recommendation and has been intensively studied. Previous traffic prediction …