Timely and accurate traffic speed predictions are an important part of the Intelligent
Transportation System (ITS), which provides data support for traffic control and guidance …

With the advancement of automatic driving and smart city, it is critical to predict traffic
information for traffic management, traffic planning, and traffic safety. When predicting traffic …

Multi‐step prediction of long‐term traffic speed is an important part of the intelligent
transportation system. Traffic speed is affected by temporal features, spatial features, and …

Short-term traffic speed prediction is fundamental to intelligent transportation systems (ITS),
and the accuracy of the model largely determines the performance of real-time traffic control …

Traffic speed prediction is a crucial and challenging task for intelligent transportation
systems. The prediction task can be accomplished via graph neural networks with structured …

Traffic speed prediction plays a significant role in the intelligent traffic system (ITS). However,
due to the complex spatial-temporal correlations of traffic data, it is very challenging to …

To overcome the drawbacks of current traffic network speed prediction methods, such as the
lack of accuracy and stability for medium and long period prediction, as well as the low …

Recently, the remarkable effect of applying Dynamic Graph Neural Networks (DGNNs) to
traffic speed prediction has received wide attention. Existing DGNN-based researches …

Real-time traffic speed prediction is an essential component of intelligent transportation
systems applications on large-scale urban networks, eg, proactive traffic management …

Short-term traffic speed prediction is a key component of proactive traffic control in the
intelligent transportation systems. The objective of this study is to investigate the short-term …