Traffic flow prediction is an important research problem in many of the Intelligent
Transportation Systems (ITS) applications. The use of Autoregressive Integrated Moving …

Background Accurate prediction of traffic flow is an integral component in most of the
Intelligent Transportation Systems (ITS) applications. The data driven approach using Box …

Short term traffic flow forecasting has received sustained attention for its ability to provide the
anticipatory traffic condition required for proactive traffic control and management. Recently …

The traffic flow prediction plays a key role in modern Intelligent Transportation Systems (ITS).
Although great achievements have been made in traffic flow prediction, it is still a challenge …

In this paper, an aggregation approach is proposed for traffic flow prediction that is based on
the moving average (MA), exponential smoothing (ES), autoregressive MA (ARIMA), and …

We develop a Kalman filter for predicting traffic flow at urban arterials based on data
obtained from connected vehicles. The proposed algorithm is computationally efficient and …

Real-time traffic flow forecasting is one of important issues of ITS research. Some forecasting
models including history average, time-series, Kalman filtering, non-parametric regression …

Given the importance of continuous traffic flow forecasting in most of Intelligent
Transportation Systems (ITS) applications, where every new traffic data become available in …

Short‐term traffic flow forecasting is a fundamental and challenging task since it is required
for the successful deployment of intelligent transportation systems and the traffic flow is …

The literature on short-term traffic flow forecasting has undergone great development
recently. Many works, describing a wide variety of different approaches, which very often …