Urban flooding has become an increasingly frequent and fatal natural hazard and numerical
modeling techniques play a vital role in its prediction and management. We review urban …

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 …

Recently connected vehicle (CV) technology has received significant attention thanks to
active pilot deployments supported by the US Department of Transportation (USDOT). At …

Network macroscopic fundamental diagrams (NMFD) and related network-level traffic
dynamics models have received both theoretical support and empirical validation with the …

This paper shows that a macroscopic fundamental diagram (MFD) relating average flow and
average density must exist on any street with blocks of diverse widths and lengths, but no …

We propose a novel approach for network-wide traffic state prediction where the statistical
time series model ARIMA is used to postprocess the residuals out of the fundamental …

It is postulated that lane-changing vehicles create voids in traffic streams, and that these
voids reduce flow. This mechanism is described with a model that tracks lane changers …

Traffic energy consumption estimation is significant for the sustainable transportation.
However, it is difficult to directly employ macro traffic flow data to accurately estimate the …

This paper aims to cross-compare existing estimation methods for the Macroscopic
Fundamental Diagram. Raw data are provided by a mesoscopic simulation tool for two …

This paper introduces a parsimonious theory for congested freeway traffic that describes the
spontaneous appearance of oscillations and their ensuing transformation into stop-and-go …