Traffic prediction plays a crucial role in alleviating traffic congestion which represents a
critical problem globally, resulting in negative consequences such as lost hours of additional …

Deep learning, a branch of machine learning, is a frontier for artificial intelligence, aiming to
be closer to its primary goal—artificial intelligence. This paper mainly adopts the summary …

Graph neural networks (GNNs) have been extensively used in a wide variety of domains in
recent years. Owing to their power in analyzing graph-structured data, they have become …

Accurate traffic forecasting is critical in improving safety, stability, and efficiency of intelligent
transportation systems. Despite years of studies, accurate traffic prediction still faces the …

With the fast development of various positioning techniques such as Global Position System
(GPS), mobile devices and remote sensing, spatio-temporal data has become increasingly …

Intelligent transportation (eg, intelligent traffic light) makes our travel more convenient and
efficient. With the development of mobile Internet and position technologies, it is reasonable …

Region-level demand forecasting is an essential task in ridehailing services. Accurate ride-
hailing demand forecasting can guide vehicle dispatching, improve vehicle utilization …

Transportation systems operate in a domain that is anything but simple. Many exhibit both
spatial and temporal characteristics, at varying scales, under varying conditions brought on …

With deepening urbanization and Internet of Vehicles (IoV) applications, the number of
private cars has been increasing in recent years. However, because the surging number of …

The task of travel time estimation (TTE), which estimates the travel time for a given route and
departure time, plays an important role in intelligent transportation systems such as …