Real-time traffic states and origin-destination (OD) flows are essential inputs for on-line
traffic control and management systems. With the final goal to unify the problem of real-time …

A general approach to the real-time estimation of the complete traffic state in freeway
stretches is developed based on the extended Kalman filter. First, a general stochastic …

Traffic state estimation is important input to traffic information and traffic management
systems. A wide variety of traffic state estimation methods exist, either data-driven or model …

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 …

Current or historic traffic states are essential input to advanced traveler information, dynamic
traffic management, and model predictive control systems. As traffic states are usually not …

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 …

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 …

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 …

This paper reports on real-data results for a real-time freeway traffic state estimator with
particular focus on its adaptive features. The pursued general approach to the real-time …

Traffic state estimators (TSEs) based on the cell transmission model (CTM) are vulnerable to
biased initial estimates of traffic flow parameters, in particular the critical density. For …