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 …

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 …

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 …

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 …

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

Accurate traffic flow forecasting (TFF) is significant for mitigating traffic congestion. To
address the existing issues of calculation and storage in dealing with big traffic flow data …

Accurate short-term traffic flow forecasting has become a crucial step in the overall goal of
better road network management. Previous research [H. Kirby, M. Dougherty, S. Watson …

Short‐term prediction of passenger flow is very important for the operation and management
of a rail transit system. Based on the traditional Kalman filtering method, this paper puts …

This paper proposes a Kalman Filter (KF) technique to predict the short-term flow at urban
arterials based on the information of connected and Bluetooth equipped vehicles. Online …

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 …