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 …

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 proposes a new stochastic model of traffic dynamics in Lagrangian coordinates.
The source of uncertainty is heterogeneity in driving behavior, captured using driver-specific …

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

Cell-phones equipped with a global positioning system (GPS) provide new opportunities for
location-based services and traffic estimation. When traveling on-board vehicles, these …

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 …

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 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 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 …

Given the importance of continuous traffic flow forecasting in most of Intelligent
Transportation Systems (ITS) applications, where every new traffic data become available in …