Traffic state estimation (TSE) refers to the process of the inference of traffic state variables
(ie, flow, density, speed and other equivalent variables) on road segments using partially …

The broad research thematic of flows on networks was addressed in recent years by many
researchers, in the area of applied mathematics, with new models based on partial …

Traffic prediction is a core problem in the intelligent transportation system and has broad
applications in the transportation management and planning, and the main challenge of this …

Traffic waves are phenomena that emerge when the vehicular density exceeds a critical
threshold. Considering the presence of increasingly automated vehicles in the traffic stream …

We develop a deep learning model to predict traffic flows. The main contribution is
development of an architecture that combines a linear model that is fitted using ℓ 1 …

Under the pressure of climate change, the demands for alternative green hydrogen (H 2)
production methods have been on the rise to conform to the global trend of transition to a H …

In this paper, we combine the most complete record of daily mobility, based on large-scale
mobile phone data, with detailed Geographic Information System (GIS) data, uncovering …

Just as it has irrevocably reshaped social life, the fast growth of smartphone ownership is
now beginning to revolutionize the driving experience and change how we think about …

Estimating and predicting traffic conditions in arterial networks using probe data has proven
to be a substantial challenge. Sparse probe data represent the vast majority of the data …

Estimates of road speeds have become commonplace and central to route planning, but few
systems in production provide information about the reliability of the prediction. Probabilistic …