New technologies able to register vehicle trajectories, such as GPS (Global Position
Systems)-enabled cell phones, have opened a new way of collecting traffic data. However …

Because microscopic models are heavily used in applications, the appropriate calibration
and validation of these models have been a recent concern. The contribution of this paper is …

Modern traffic control and management systems in urban networks require real-time
estimation of the traffic states. In this paper, a novel approach for modeling traffic flow in …

The estimation of traffic flow variables (flow, space mean speed and density) plays a
fundamental role in highways planning and designing, as well as in traffic control strategies …

With more connected vehicles (CVs) in the networks, the big data era leads to the availability
of abundant data from CVs. CV penetration rate is the fundamental building block of …

In real-time traffic management and intelligent transportation systems (ITS) applications, an
accurate picture of the prevailing traffic state in terms of speeds and densities is critical, for …

Real‐time traffic state estimation is of importance for efficient traffic management. This is
especially the case for traffic management systems that require fast detection of changes in …

Freeway traffic state estimation and prediction are central components in real-time traffic
management and information applications. Model-based traffic state estimators consist of a …

Validating microscopic traffic simulation models incorporates several challenges because of
the inadequacy and rareness of validation data, and the complexity of the car following and …

This study proposes a state-space model that estimates traffic states over a two-dimensional
network with alternative routes available by a data assimilation technique that fuses probe …