The objective of this paper is to present a new analytical tool that predicts highway
congestion in real time by utilizing a macroscopic traffic flow model, and to investigate a data …

Lagrangian Traffic model which follows a platoon of vehicle has the benefit of convenient
utilization of individual vehicle data and easy distribution of traffic information to the drivers …

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 …

The paper presents a unified macroscopic model-based approach to real-time freeway
network traffic surveillance as well as a software tool RENAISSANCE that has been recently …

This paper presents a novel approach for freeway traffic state estimation. Although there is
currently a wide variety of estimation methods, new designs and technologies can still be …

Traffic congestion caused by either insufficient road capacity or unexpected events has been
a major problem in urban transportation networks. To disseminate accurate traveler …

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 …

Recent researches have shown the potential benefits of using Lagrangian coordinates in
modeling mobile sensor data such as GPS, Bluetooth, Wi-Fi, and cellphone probe data …

Freeway traffic state estimation and prediction are central components in real-time traffic
management and information applications. Model-based traffic state estimators consist of a …

Intelligent Transportation Systems (ITS) have been considered important technologies to
mitigate urban traffic congestion. Accurate traffic prediction is one of the critical steps in the …