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 …

With the recent advances in radio-frequency identification (RFID), low-cost wireless sensor
devices, and Web technologies, the Internet of Things (IoT) approach has gained …

Taxi demand prediction has recently attracted increasing research interest due to its huge
potential application in large-scale intelligent transportation systems. However, most of the …

Predicting taxi demand throughout a city can help to organize the taxi fleet and minimize the
wait-time for passengers and drivers. In this paper, we propose a sequence learning model …

Taxi-calling apps are gaining increasing popularity for their efficiency in dispatching idle
taxis to passengers in need. To precisely balance the supply and the demand of taxis, online …

Informed driving is increasingly becoming a key feature for increasing the sustainability of
taxi companies. The sensors that are installed in each vehicle are providing new …

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 …

The development of a city gradually fosters different functional regions, such as educational
areas and business districts. In this paper, we propose a framework (titled DRoF) that …

As increasing volumes of urban data are captured and become available, new opportunities
arise for data-driven analysis that can lead to improvements in the lives of citizens through …

Taxi ridesharing can be of significant social and environmental benefit, eg by saving energy
consumption and satisfying people's commute needs. Despite the great potential, taxi …