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 analysis of big data is deemed to define a new era in urban research, planning and
policy. Real-time data mining and pattern detection in high-frequency data can now be …

This study aims to combine the modeling skills of deep learning and the domain knowledge
in transportation into prediction of metro passenger flow. We present an end-to-end deep …

Abstract With Green Deals and a competitive techno-economic basis for low-carbon energy
transitions, energy infrastructural change is intensifying. This is matched by rapid growth in …

Evidence suggests that the proportion of the human population living in cities will continue to
grow, to the point where over 90% of the worldLs population will be living in one form of city …

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

Smart card data gathered by automated fare collection (AFC) systems are valuable
resources for studying urban mobility. In this paper, we propose two approaches to cluster …

Polycentric urban development is gaining momentum in both scholarly research and real-life
practice. This brings new demand for planning support systems to simulate and analyse the …

This book has emerged through years of discussions, comments and questions we have
received about building agentbased models and integrating geographical information …