We provide a brief review of human mobility science and present three key areas where we
expect to see substantial advancements. We start from the mind and discuss the need to …

The rapid development in machine learning and in the emergence of new data sources
makes it possible to examine and predict traffic conditions in smart cities more accurately …

The sustainable governance of transport systems remains a significant challenge for policy
makers worldwide, particularly in cities. Urban areas are develo** rapidly from a …

Reliable and accurate short-term subway passenger flow prediction is important for
passengers, transit operators, and public agencies. Traditional studies focus on regular …

The complexity of cities and their internal structure make it more and more important to study
the distribution of urban population density, and big data provide some new technical means …

The primary objective of this study is to identify the spatio-temporal relationship between
metro ridership and built environment by integrating smart card data with online point of …

To discover regularities in human mobility is of fundamental importance to our
understanding of urban dynamics, and essential to city and transport planning, urban …

Large-scale GPS location datasets hold immense potential for measuring human mobility
and interpersonal contact, both of which are essential for data-driven epidemiology …

As cities continuously expand and with the emergence of mega-city regions, the urban
functional zones (UFZs) have spread beyond their original administrative boundaries. An …

For intelligent urban transportation systems, the ability to predict individual mobility is crucial
for personalized traveler information, targeted demand management, and dynamic system …