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 …

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 …

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 …

Real-time traffic flow estimation is important for online traffic control and management. The
traffic state estimator optimally matches traffic measurements from detectors with traffic flow …

Traffic state estimation is a challenging problem for the transportation community due to the
limited deployment of sensing infrastructure. However, recent trends in the mobile phone …

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 …

We present a comparison for several filter configurations for freeway traffic state estimation.
Since the environmental conditions on a freeway may change over time (eg, changing …

This paper presents a case study of real-time traffic state estimation. The adopted general
approach to the design of universal traffic state estimators for freeway stretches is based on …

This paper presents a real-time freeway network traffic surveillance tool RENAISSANCE.
Based on a stochastic macroscopic freeway network traffic flow model and the extended …

In real-time traffic management and intelligent transportation systems (ITS) applications, an
accurate picture of the prevailing traffic state in terms of speeds and densities is critical, for …