Today, a new generation of artificial intelligence has brought several new research domains
such as computer vision (CV). Thus, target tracking, the base of CV, has been a hotspot …

Short-term passenger demand forecasting is of great importance to the on-demand ride
service platform, which can incentivize vacant cars moving from over-supply regions to over …

Neural networks have been extensively applied to short-term traffic prediction in the past
years. This study proposes a novel architecture of neural networks, Long Short-Term Neural …

Since the early 1980s, short-term traffic forecasting has been an integral part of most
Intelligent Transportation Systems (ITS) research and applications; most effort has gone into …

The k-nearest neighbor (KNN) model is an effective statistical model applied in short-term
traffic forecasting that can provide reliable data to guide travelers. This study proposes an …

We propose a novel approach for network-wide traffic state prediction where the statistical
time series model ARIMA is used to postprocess the residuals out of the fundamental …

Short-term traffic flow prediction is a critical aspect of Intelligent Transportation System.
Timely and accurate traffic forecasting results are necessary inputs for advanced traffic …

Short-term prediction is one of the essential elements of intelligent transportation systems
(ITS). Although fine prediction methodologies have been reported, most prediction methods …

Road traffic speed prediction is a challenging problem in intelligent transportation system
(ITS) and has gained increasing attentions. Existing works are mainly based on raw speed …

Road traffic prediction is a critical component in modern smart transportation systems. It
provides the basis for traffic management agencies to generate proactive traffic operation …