Variable techniques have been used to collect traffic data and estimate traffic conditions. In
most cases, more than one technology is available. A legitimate need for research and …

This research proposes a short-term highway traffic state prediction method based on a
structural state space model, with the intention to provide a robust approach for obtaining …

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 …

Traffic information from probe vehicles has great potential for improving the estimation
accuracy of traffic situations, especially where no traffic detector is installed. A method for …

Feedback approach for real-time traffic state estimation on urban road with signalized
intersection is presented. The conventional discretization of kinematic wave model for …

Traffic state prediction is a key problem with considerable implications in modern traffic
management. Traffic flow theory has provided significant resources, including models based …

The accurate depiction of the existing traffic state on a road network is essential in reducing
congestion and delays at signalized intersections. The existing literature in the optimization …

Recent advances in vehicle-based surveillance technologies using Global Positioning
Systems (GPS) promise high accuracy traffic information; however, their performance in field …

The paper validates an improved adaptive Kalman filter model (AKFM) for short-term traffic
flow prediction on intersections in Shanghai, China. In this field, much research has been …

Real-data testing results of a real-time nonlinear freeway traffic state estimator are presented
with a particular focus on its adaptive features. The pursued general approach to the real …