The advances in location-acquisition and mobile computing techniques have generated
massive spatial trajectory data, which represent the mobility of a diversity of moving objects …

Traditional trajectory anomaly detection aims to find abnormal trajectory points or sequences
using data mining techniques. As a comparison, we focus on the evaluation of the …

Forecasting the flow of crowds is of great importance to traffic management and public
safety, and very challenging as it is affected by many complex factors, including spatial …

Urbanization's rapid progress has modernized many people's lives but also engendered big
issues, such as traffic congestion, energy consumption, and pollution. Urban computing …

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 …

In recent years, there has been increased interest in using completely anonymized data from
smart card collection systems to better understand the behavioural habits of public transport …

As the development of crowdsourcing technique, acquiring amounts of data in urban cities
becomes possible and reliable, which makes it possible to mine useful and significant …

Metro systems have become one of the most important public transit services in cities. It is
important to understand individual metro passengers' spatio-temporal travel patterns. More …

Traffic congestion is a condition of a segment in the road network where the traffic demand is
greater than the available road capacity. The detection of unusual traffic patterns including …

In this paper, we present a visual analysis system to explore sparse traffic trajectory data
recorded by transportation cells. Such data contains the movements of nearly all moving …