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 …

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 …

ABSTRACT New Big Data sources such as mobile phone call data records, smart card data
and geo-coded social media records allow to observe and understand mobility behaviour on …

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 …

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

Cellular signaling data provide a massive and emerging source for acquiring urban origin–
destination (OD) travel flow information, supporting decision making on large-scale mobility …

Activity-based travel demand models are becoming essential tools used in transportation
planning and regional development scenario evaluation. They describe travel itineraries of …

Understanding and correctly modeling urban mobility is a crucial issue for the development
of smart cities. The estimation of individual trips from mobile phone positioning data (ie, call …

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 …

Passively generated mobile phone dataset is emerging as a new data source for research in
human mobility patterns. Information on individuals' trajectories is not directly available from …