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 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 …

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 …

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

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 …

Connected and autonomous vehicles (CAVs) are on the way to the field application. In the
beginning stage, there will be a mixed traffic flow, containing the regular human‐driven …

Two models employing Kalman filtering theory are proposed for predicting short-term traffic
volume. Prediction parameters are improved using the most recent prediction error and …

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 …

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

The sustainable growth of cities created the need for better informed decisions based on
information and communication technologies to sense the city and quantify its pulse. An …