Due to the ubiquity of mobile phones, mobile phone network data (eg, Call Detail Records,
CDR; and cellular signaling data, CSD), which are collected by mobile telecommunication …

The rapid development in telecommunication networks is producing a huge amount of
information regarding how people (with their mobile devices) move and behave over space …

Mobile phone data collected by network operators can provide fundamental insights into
individual and aggregate mobility of people, at unprecedented spatiotemporal scales …

Call detail records (CDR) collected by mobile phone network providers have been largely
used to model and analyze human-centric mobility. Despite their potential, they are limited in …

With the widespread application of mobile phones, it has become possible to study human
mobility and travel behaviors based on cellular network data. Contrary to call detail records …

Passively-generated data, such as GPS data and cellular data, bring tremendous
opportunities for human mobility analysis and transportation applications. Since their …

Identifying and detecting the travel mode and pattern of individual travelers is an important
problem in transportation planning and policy making. Mobile-phone Signaling Data (MSD) …

Spatiotemporal data, and more specifically origin–destination matrices, are critical inputs to
mobility studies for transportation planning and urban management purposes. Traditionally …

Fast urbanization generates increasing amounts of travel flows, urging the need for efficient
transport planning policies. In parallel, mobile phone data have emerged as the largest …

Transportation mode inference is an important research direction and has many
applications. Existing methods are usually based on fine-grained sampling-collecting …