This paper reviews the activity-travel behaviour literature that employs Machine Learning
(ML) techniques for empirical analysis and modelling. Machine Learning algorithms, which …

Abstract Purpose of Review To review the literature on built environment interventions to
increase active travel, focusing on work since 2000 and on methodological choices and …

Elevation datasets (eg point clouds) are an essential but often unavailable ingredient for the
construction of 3D city models. We investigate in this paper to what extent can 3D city …

The past few years have witnessed the rapid growth in the collection of large-scale GPS
data via smartphone-based travel surveys around the world, following which transportation …

Data mining is the science of extracting information or “knowledge” from data. It is a task
commonly executed on cloud computing resources, personal computers and laptops …

Abstract Knowledge about what transport mode people use is important information of any
mobility or travel behaviour research. With ubiquitous presence of smartphones, and its …

Urban mobility plays an important role in addressing urban livability. The complexification
and dispersion of travel due to the improvement of transport and the multiplication of our …

With the rapid development of mobile Internet techniques, using the sensor-rich
smartphones to sense various contexts attracts much attention, such as transportation mode …

Transportation planning and solutions have an enormous impact on city life. To minimize the
transport duration, urban planners should understand and elaborate the mobility of a city …

Where GPS technology can precisely register the spatiotemporal elements of activity-travel
behaviour, travel characteristics need to be imputed from the data. As such, throughout the …