Accurate and real-time traffic passenger flows forecasting at transportation hubs, such as
subway/bus stations, is a practical application and of great significance for urban traffic …

Accurate urban traffic prediction is a critical issue in Intelligent Transportation Systems (ITS).
It is challenging since urban traffic usually indicates high dynamic spatio-temporal …

The rapid urbanization and continuous improvement of road traffic equipment result in
massive daily production of traffic data. These data contain the long-term evolution of traffic …

As a typical problem in time series analysis, traffic flow prediction is one of the most
important application fields of machine learning. However, achieving highly accurate traffic …

Forecasting the traffic flows is a critical issue for researchers and practitioners in the field of
transportation. However, it is very challenging since the traffic flows usually show high …

Traffic flow analysis, prediction and management are keystones for building smart cities in
the new era. With the help of deep neural networks and big traffic data, we can better …

Graph convolutional networks (GCN) have been applied in the traffic flow forecasting tasks
with the graph capability in describing the irregular topology structures of road networks …

The prediction of crowd flows is an important urban computing issue whose purpose is to
predict the future number of incoming and outgoing people in regions. Measuring the …

Accurate and real-time traffic forecasting plays an important role in the intelligent traffic
system and is of great significance for urban traffic planning, traffic management, and traffic …

Traffic flow prediction effectively supports the sustainable expansion and operation of
modern transport networks, one of the emerging research areas in intelligent transportation …