Traffic prediction plays a crucial role in alleviating traffic congestion which represents a
critical problem globally, resulting in negative consequences such as lost hours of additional …

Traffic management is improved in cutting-edge smart cities using technologies such as
machine learning and deep learning to streamline daily tasks and boost productivity …

By leveraging the conventional Vehicular Ad-hoc Networks (VANETs), the Internet of
Vehicles (IoV) paradigm has attracted the attention of different research and development …

Building type prediction is a critical task for urban planning and population estimation. The
growing availability of multi-source data presents rich semantic information for building type …

Collection and analysis of traffic data are the most critical challenges in traffic control in
transportation networks. The dramatic growth of new technologies such as tiny devices …

In order to solve the problem of urban short-term traffic congestion and temporal and spatial
heterogeneity, it is important to scientifically delineate urban traffic congestion response …

Traffic state estimation is an essential task in traffic engineering. It requires observations of
traffic that are, so far, even with emerging technologies, only partially available at large, as …

The primary goal with which any transportation system is designed is to make efficient use of
the available infrastructure to achieve better level of service (LoS). However, LoS is …

Non-recurrent congestion disrupts normal traffic operations and lowers travel time (TT)
reliability, which leads to many negative consequences such as difficulties in trip planning …

The blurring of industry lines, or the phenomenon of new products or industries crossing
over, is becoming more common. Academic circles have taken notice of this phenomenon …