Traffic speed prediction is a critically important component of intelligent transportation
systems. Recently, with the rapid development of deep learning and transportation data …

In recent years, the convolutional and recurrent neural networks are widely applied in traffic
prediction tasks. Traffic speed prediction is an important and challenging topic in intelligent …

Speed prediction is a crucial yet complicated task for intelligent transportation systems. The
challenge derives from the complex spatiotemporal dependencies of traffic parameters. In …

Timely and accurate traffic speed prediction has gained increasing importance for urban
traffic management and helping one to make advisable travel decision. However, the …

Accurate and robust short-term traffic prediction is an important part of advanced traveler
information systems. With the development of intelligent navigation and autonomous driving …

Increasingly serious traffic congestion requires an accurate and timely traffic speed
prediction, which will significantly benefit both individual drivers and decision makers in …

Short-term traffic forecasting based on deep learning methods, especially long short-term
memory (LSTM) neural networks, has received much attention in recent years. However, the …

Traffic prediction, as an important part of intelligent transportation systems, plays a critical
role in traffic state monitoring. While many studies accomplished traffic forecasting task with …

Short‐term traffic speed prediction is a promising research topic in intelligent transportation
systems (ITSs), which also plays an important role in the real‐time decision‐making of traffic …

As an important part of the intelligent transportation system (ITS), short‐term traffic prediction
has become a hot research topic in the field of traffic engineering. In recent years, with the …