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

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 …

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 …

Around half of the world population is living in cities where different transportation networks
are cooperating together to provide some efficient transportation facilities for individuals. To …

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 …

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

In this study, with Estonia as an example, we established an approach based on Hidden
Markov Model to extract large-scale commuting patterns at different geographical levels …

The signaling data in cellular networks provide means for analyzing the use of transportation
systems. We propose methods that aim to reconstruct the used route through a …

Cellular networks of today generate a massive amount of signalling data. A large part of this
signalling is generated to handle the mobility of subscribers and contains location …

Mobile cellular networks can serve as ubiquitous sensors for physical mobility. We propose
a method to infer vehicle travel times on highways and to detect road congestion in real …