The rapid development of intelligent transport systems (ITS) has increased the need to
propose advanced methods to predict traffic information. These methods play an important …

Short-term traffic prediction can be defined as the process of estimating the anticipated traffic
conditions in the short-term future given historical and current traffic information (Vlahogianni …

A multitude of challenges confront Intelligent Transport Systems (ITS) due to the rapid
growth in demand for wireless connectivity, the more diverse and het-erogeneous nature of …

Accurate and timely traffic forecasting is crucial to effective management of intelligent
transportation systems (ITS). To predict travel time index (TTI) data, we select six baseline …

Deep learning has achieved good performance in short-term traffic forecasting recently.
However, the stochasticity and distribution imbalance are main characteristics to traffic flow …

Short-term traffic flow forecasting is a key element in Intelligent Transport Systems (ITS) to
provide proactive traffic state information to road network operators. A variety of methods to …

Accurate and timely forecasting of traffic status is crucial to effective management of
intelligent transportation systems (ITS). An interacting multiple model (IMM) predictor is …

The increase of road traffic in large cities during the last years has produced that long and
short-term traffic flow forecasting is a critical need for the authorities. The availability of good …

Nowadays, accurate and efficient short-term traffic flow forecasting plays a critical role in
intelligent transportation systems (ITS). However, due to the fact that traffic flow is …

Long short-term memory (LSTM) models provide high predictive performance through their
ability to recognize longer sequences of time series data. More recently, bidirectional deep …