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 …

Big data and business analytics are trends that are positively impacting the business world.
Past researches show that data generated in the modern world is huge and growing …

Fast urbanization generates increasing amounts of travel flows, urging the need for efficient
transport planning policies. In parallel, mobile phone data have emerged as the largest …

By developing cities and increasing population, smart transportation becomes an essential
component of modern societies. Extensive research activities using machine learning …

Even though a variety of human mobility models have been recently developed, models that
can capture real-time human mobility of urban populations in a sustainable and economical …

Traffic flow prediction based on vehicle trajectories collected from the installed GPS devices
is critically important to Intelligent Transportation Systems (ITS). One limitation of existing …

This study deals with urban transport network flow estimation based on Cellphone Location
(CL) and License Plate Recognition (LPR) data. We first propose two methods to filter CL …

Passively-generated mobile phone data is emerging as a potential data source for
transportation research and applications. Despite the large amount of studies based on the …

Understanding the travel behaviors and activity patterns of vulnerable people is important for
addressing social equity in urban and transportation planning. With the increasing …

New digital technologies have empowered companies to make use of tools to produce
insights for key supply chain processes. Resilience, the property of supply chains to respond …