Citizens are increasingly sharing their location and movements through “check-ins” on
location based social networks (LBSNs). These services are collecting unprecedented …

A growing body of literature has been devoted to harnessing the crowdsourcing power of
social media by extracting knowledge from the huge amounts of information available …

Long-distance trips are less frequent than short-distance urban trips, but contribute
significantly to the total distance traveled, and thus to congestion and transport-related …

Travel surveys complemented by additional land use and socio-economic data have served
as primary inputs for travel demand models. A complete household survey with all the …

The rise of technology and the internet provides powerful means for people from all around
the world to communicate and connect with one another. Online social network platforms …

Technological advances have led to an increasing development of data sources. Since the
introduction of social networks, numerous studies on the relationships between users and …

Predicting the future activity location and trajectory of residents can provide essential
information for smart urban management such as epidemic control, traffic facilitation, public …

This article describes how understanding human mobility behavior is of great significance
for predicting a broad range of socioeconomic phenomena in contemporary society …

Travel demand modeling has evolved from the traditional four-step models to tour-based
models which eventually became the basis of the advanced Activity-Based Models (ABM) …

Understanding and predicting human mobility is a crucial component of a range of
administrative activities, from transportation planning to tourism and travel management. In …