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

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 …

This paper reports on real data testing of a real-time freeway traffic state estimator, with a
particular focus on its adaptive capabilities. The pursued general approach to the real-time …

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

This paper formulates the traffic flow forecasting task by introducing a maximum correntropy
deduced Kalman filter. The traditional Kalman filter is based on minimum mean square error …

Frequent traffic congestion and gridlocks are causing global economies staggering cost in
terms of fuel consumption, time wastage, and public health. To rectify this problem, many …

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 …

This paper addresses the problem of freeway traffic flow estimation. The freeway is
considered as a network of components representing different freeway stretches called …

This paper presents a case study of real-time traffic state estimation. The adopted general
approach to the design of universal traffic state estimators for freeway stretches is based on …