In this paper, we use a cell transmission model based switching state-space model to
estimate vehicle densities and congestion modes at unmeasured locations on a highway …

We present our latest results on developing and implementing a traffic congestion mode and
vehicle density estimator for a segment of Interstate 210 in Southern California. Using a …

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 presents a traffic state estimation and prediction model based on the cell
transmission model (CTM). The nonlinear CTM is transcribed in a closed analytical state …

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 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 …

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 …

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 …

The number of vehicles included in a metered motorway ramp or an urban signalized link at
any time is valuable information for real-time control. A Kalman-Filter is employed to produce …

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 …