In the present research, a nonlinear Kalman filtering approach, ie, extended Kalman filter
(EKF) was proposed to solve dynamic OD flows and travel times on a freeway segment. The …

The purpose of this research is to develop a dynamic model for on-line estimation and
prediction of freeway origin-destination (OD) demands. Time-dependent OD matrices are …

In order to meet the need of traffic route guidance and traffic monitoring system in urban
areas, this paper introduces a method to estimate and predict traffic condition and travel time …

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 model was formulated for estimating dynamic origin-destination (OD) travel time and flow
on a long freeway with a neural Kalman filter originally developed by the authors. The model …

The urban traffic usually has the characteristics of time-variation and nonlinearity, real-time
and accurate traffic flow forecasting has become an important component of the Intelligent …

The forecasting of traffic flow is an important thesis of the research of intelligent
transportation systems (ITS). A good method of traffic flow forecasting can play a very …

In order to give full play to the overall efficiency of freeway networks and raise the level of
operation and service, freeway management is faced with higher requirements and greater …

This paper presents a new approach for dynamic estimation of origin-destination (OD)
matrices based on Unscented Kalman Filter (UKF). The new approach, differs from most of …

Real time traffic state estimation is important to facilitate better traffic management in urban
areas and is a prime concern from a traffic engineer's viewpoint. Traffic density is a key traffic …