Unsupervised learning (UL) has a long and successful history in untangling the complexity
of cities. As the counterpart of supervised learning, it discovers patterns from intrinsic data …

Human mobility is subject to collective dynamics that are the outcome of numerous
individual choices. Smart card data which originated as a means of facilitating automated …

The previous technology-centric development of smart cities mainly focuses on the numbers,
diversities, and types of applied intelligent technologies, while the citizen-centric smart city …

Understanding tourist mobility patterns of demographic subgroups is vital to tourism
planning and management. However, existing empirical studies used various indicators and …

Transit-oriented development (TOD) aims to create pedestrian-friendly neighborhoods
around transit hubs to improve urban mobility. However, it often overlooks the specific …

Regularity is an important property of individual travel behaviour. The ability to measure it
enables advances in behaviour modelling, mobility prediction and commuter analytics. The …

The metro station ridership features are associated significantly with the built environment
factors of the pedestrian catchment area surrounding metro stations. The existing studies …

This paper aims to analyse the factors that influence the behaviour in relation to bus line shift
with the support of large-scale smart card datasets, focussing on a case study of the public …

The travel mobility gap is among the indicators that can be used to evaluate the level of
social and transport inequity. To achieve a large and representative sample for this …

Multidimensional inequalities have been increasingly discussed in the transportation field,
particularly in the case of bike riding. Although several studies focused on the gender …