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 …

Traffic congestion occurs when traffic demand is greater than the available network capacity.
It is characterized by lower vehicle speeds, increased travel times, arrival unreliability, and …

Even though a variety of human mobility models have been recently developed, models that
can capture real-time human mobility of urban populations in a sustainable and economical …

This study deals with urban transport network flow estimation based on Cellphone Location
(CL) and License Plate Recognition (LPR) data. We first propose two methods to filter CL …

Aiming to develop a theoretically consistent framework to estimate travel demand using
multiple data sources, this paper first proposes a multi-layered Hierarchical Flow Network …

Tracking the source of congestion, namely where the congested traffic flow comes from and
goes to, is a key prerequisite to understanding the causes of traffic congestion and facilitates …

This paper proposes a privacy-preserving data fusion method for traffic state estimation
(TSE). Unlike existing works that assume all data sources to be accessible by a single …

Dynamic vehicular origin–destination (OD) flow is a fundamental component of traffic
network modeling and its estimation has long been studied. Although ideal observing …

Evacuation behavior models estimated using post-disaster surveys are not adequate to
predict real-time dynamic population response as a hurricane unfolds. With the emergence …

Accurate occupancy is crucial for planning for sustainable buildings. Using massive,
passively-collected mobile phone data, we introduce a novel framework to estimate building …