This article addresses the question of how planners' use and non-use of expert knowledge
affect the content and goal achievement potential of plans, and discusses how changes in …

Advances in Data Science permeate every field of Transportation Science and Engineering,
resulting in developments in the transportation sector that are data-driven. Nowadays …

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 …

Mobile data has allowed us to sense urban dynamics at scales and granularities not known
before, helping urban planners to cope with urban growth. A frequently used kind of dataset …

The rapid, unplanned urbanisation in Haiti creates a series of urban mobility challenges
which can contribute to job market fragmentation and decrease the quality of life in the city …

In human relations individuals' gender and age play a key role in the structures and
dynamics of their social arrangements. In order to analyze the gender preferences of …

Several studies have pointed to the difficulties of obtaining good data on train ridership.
There are at least two challenges regarding these data. First, train operators consider such …

In this work, we propose a novel approach to reconstruct the individual's trajectories that has
been extracted from Call Details Records (CDR) and Visitor Location Registry (VLR) data …

As mobile phone technology evolves quickly, people could use mobile phones to conduct
business, watch entertainment shows, order food, and many more. These location-based …

The fast development of information and communication technologies has engendered a
massive generation of mobile data with great potential for extracting mobility patterns and …