Intelligent Transportation Systems

The Kalman filter (KF) is a state estimation algorithm that optimally combines system knowledge and measurements to minimize the mean squared error of the estimated states. While KF was initially designed for linear systems, numerous extensions of it, such as extended Kalman filter (EKF), unscented Kalman filter (UKF), cubature Kalman filter (CKF), etc., have been proposed for nonlinear systems over the last sixty years. Although different types of nonlinear KFs have different pros and cons, they all use the same framework of linear KF. Yet, according to our theoretical and empirical...

Technical and economic investigations of automated highway systems (AHS) are addressed. It has generally been accepted that such systems show potential to alleviate urban traffic congestion, so most of the AHS research has been focused instead on technical design and implementation issues. It is demonstrated that, despite making a number of assumptions that are favorable to AHS, the actual viable implementation opportunities for AHS are scarce, and that most existing congested urban areas can be disqualified on the basis of at least one criterion developed herein. Technical investigations...

Automotive traffic monitoring using probe vehicles with Global Positioning System receivers promises significant improvements in cost, coverage, and accuracy. Current approaches, however, raise privacy concerns because they require participants to reveal their positions to an external traffic monitoring server. To address this challenge, we propose a system based on virtual trip lines and an associated cloaking technique. Virtual trip lines are geographic markers that indicate where vehicles should provide location updates. These markers can be placed to avoid particularly privacy...

This article investigates the problem of incorporating mobile probe data collected from GPS equipped cell phones into estimation algorithms for travel time. We use kinematic wave theory to create a modeling framework capable of incorporating trajectory data into the model. The problem of including loop detector data in this model is performed using a standard approach available in the literature. The problem of fusing this data with probe data is formulated using the Moskowitz function, which results from kinematic wave theory. Using this formulation, two linear programs are posed to...